In this contribution, we develop a novel global threshold-based active contour model. This model deploys a new
edge-stopping function to control the direction of the evolution and to stop the evolving contour at weak or
blurred edges. An implementation of the model requires the use of selective binary and Gaussian filtering
regularized level set (SBGFRLS) method. The method uses either a selective local or global segmentation
property. It penalizes the level set function to force it to become a binary function. This procedure is followed by
using a regularisation Gaussian. The Gaussian filters smooth the level set function and stabilises the evolution
process. One of the merits of our proposed model stems from the ability to initialise the contour anywhere inside
the image to extract object boundaries. The proposed method is found to perform well, notably when the
intensities inside and outside the object are homogenous. Our method is applied with satisfactory results on
various types of images, including synthetic, medical and Arabic-characters images.
A MORPHOLOGICAL MULTIPHASE ACTIVE CONTOUR FOR VASCULAR SEGMENTATIONijbbjournal
This paper presents a morphological active contour ideal for vascular segmentation in biomedical images.
The unenhanced images of vessels and background are successfully segmented using a two-step
morphological active contour based upon Chan and Vese’s Active Contour without Edges. Using dilation
and erosion as an approximation of curve evolution, the contour provides an efficient, simple, and robust
alternative to solving partial differential equations used by traditional level-set Active Contour models. The
proposed method is demonstrated with segmented data set images and compared to results garnered from
multiphase Active Contour without Edges, morphological watershed, and Fuzzy C-means segmentations.
New geometric interpretation and analytic solution for quadrilateral reconstr...Joo-Haeng Lee
Accepted as poster presentation for ICPR 2014, Stockholm, Sweden on August 24~28, 2014.
[Revised Version]
Title: New geometric interpretation and analytic solution for quadrilateral reconstruction
Author: Joo-Haeng Lee
Affiliation: Human-Robot Interaction Research Team, ETRI, KOREA
Abstract:
A new geometric framework, called generalized coupled line camera (GCLC), is proposed to derive an analytic solution to reconstruct an unknown scene quadrilateral and the relevant projective structure from a single or multiple image quadrilaterals. We extend the previous approach developed for rectangle to handle arbitrary scene quadrilaterals. First, we generalize a single line camera by removing the centering constraint that the principal axis should bisect a scene line. Then, we couple a pair of generalized line cameras to model a frustum with a quadrilateral base. Finally, we show that the scene quadrilateral and the center of projection can be analytically reconstructed from a single view when prior knowledge on the quadrilateral is available. A completely unknown quadrilateral can be reconstructed from four views through non-linear optimization. We also describe a improved method to handle an off-centered case by geometrically inferring a centered proxy quadrilateral, which accelerates a reconstruction process without relying on homography. The proposed method is easy to implement since each step is expressed as a simple analytic equation. We present the experimental results on real and synthetic examples.
[Submitted Version]
Title: Generalized Coupled Line Cameras and Application in Quadrilateral Reconstruction
Abstract:
Coupled line camera (CLC) provides a geometric framework to derive an analytic solution to reconstruct an unknown scene rectangle and the relevant projective structure from a single image quadrilateral. We extend this approach as generalized coupled line camera (GCLC) to handle a scene quadrilateral. First, we generalize a single line camera by removing the centering constraint that the principal axis should bisect a scene line. Then, we couple a pair of generalized line cameras to model a frustum with a quadrilateral base. Finally, we show that the scene quadrilateral and the center of projection can be analytically reconstructed from a single view when prior knowledge on the quadrilateral is available. ...
Automatic rectification of perspective distortion from a single image using p...ijcsa
Perspective distortion occurs due to the perspective projection of 3D scene on a 2D surface. Correcting the distortion of a single image without losing any desired information is one of the challenging task in the field of Computer Vision. We consider the problem of estimating perspective distortion from a single still image of an unstructured environment and to make perspective correction which is both quantitatively accurate as well as visually pleasing. Corners are detected based on the orientation of the image. A method based on plane homography and transformation is used to make perspective correction. The algorithm infers frontier information directly from the images, without any reference objects or prior knowledge of the camera parameters. The frontiers are detected using geometric context based segmentation. The goal of this paper is to present a framework providing fully automatic and fast perspective correction.
Solving the Pose Ambiguity via a Simple Concentric Circle ConstraintDr. Amarjeet Singh
Estimating the pose of objects with circle feature from images is a basic and important question in computer vision
community. This paper is focused on the ambiguity problem in pose estimation of circle feature, and a new method is proposed based
on the concentric circle constraint. The pose of a single circle feature, in general, can be determined from its projection in the image
plane with a pre-calibrated camera. However, there are generally two possible sets of pose parameters. By introducing the concentric
circle constraint, interference from the false solution can be excluded. On the basis of element at infinity in projective geometry and
the Euclidean distance invariant, cases that concentric circles are coplanar and non-coplanar are discussed respectively. Experiments
on these two cases are performed to validate the proposed method.
Image segmentation Based on Chan-Vese Active Contours using Finite Difference...ijsrd.com
There are a lot of image segmentation techniques that try to differentiate between backgrounds and object pixels but many of them fail to discriminate between different objects that are close to each other, e.g. low contrast between foreground and background regions increase the difficulty for segmenting images. So we introduced the Chan-Vese active contours model for image segmentation to detect the objects in given image, which is built based on techniques of curve evolution and level set method. The Chan-Vese model is a special case of Mumford-Shah functional for segmentation and level sets. It differs from other active contour models in that it is not edge dependent, therefore it is more capable of detecting objects whose boundaries may not be defined by a gradient. Finally, we developed code in Matlab 7.8 for solving resulting Partial differential equation numerically by the finite differences schemes on pixel-by-pixel domain.
Fast Complex Gabor Wavelet Based Palmprint AuthenticationCSCJournals
A biometric system is a pattern recognition system that recognizes a person on the basis of the physiological or behavioural characteristics that the person possesses. There is increasing interest of researchers in the development of fast and accurate personal recognition systems. In this paper, Sliding window method is used to make the system fast by reducing the matching time. The reduction in computation time indirectly reduces the overall comparison time that makes the system fast. Here, 2-D Complex Gabor Wavelet method is used to extract features from palmprint. The extracted features are stored in a feature vector and matched by hamming distance similarity measurement using sliding window approach. Reduction of 74.12% and 90.32% in comparison time is achieved using Sliding window methods. The improvement in time and accuracy as indicated by experimental results makes a system rapid and accurate.
A new hybrid method for the segmentation of the brain mrissipij
The magnetic resonance imaging is a method which has undeniable qualities of contrast and tissue
characterization, presenting an interest in the follow-up of various pathologies such as the multiple
sclerosis. In this work, a new method of hybrid segmentation is presented and applied to Brain MRIs. The
extraction of the image of the brain is pretreated with the Non Local Means filter. A theoretical approach is
proposed; finally the last section is organized around an experimental part allowing the study of the
behavior of our model on textured images. In the aim to validate our model, different segmentations were
down on pathological Brain MRI, the obtained results have been compared to the results obtained by
another models. This results show the effectiveness and the robustness of the suggested approach.
A MORPHOLOGICAL MULTIPHASE ACTIVE CONTOUR FOR VASCULAR SEGMENTATIONijbbjournal
This paper presents a morphological active contour ideal for vascular segmentation in biomedical images.
The unenhanced images of vessels and background are successfully segmented using a two-step
morphological active contour based upon Chan and Vese’s Active Contour without Edges. Using dilation
and erosion as an approximation of curve evolution, the contour provides an efficient, simple, and robust
alternative to solving partial differential equations used by traditional level-set Active Contour models. The
proposed method is demonstrated with segmented data set images and compared to results garnered from
multiphase Active Contour without Edges, morphological watershed, and Fuzzy C-means segmentations.
New geometric interpretation and analytic solution for quadrilateral reconstr...Joo-Haeng Lee
Accepted as poster presentation for ICPR 2014, Stockholm, Sweden on August 24~28, 2014.
[Revised Version]
Title: New geometric interpretation and analytic solution for quadrilateral reconstruction
Author: Joo-Haeng Lee
Affiliation: Human-Robot Interaction Research Team, ETRI, KOREA
Abstract:
A new geometric framework, called generalized coupled line camera (GCLC), is proposed to derive an analytic solution to reconstruct an unknown scene quadrilateral and the relevant projective structure from a single or multiple image quadrilaterals. We extend the previous approach developed for rectangle to handle arbitrary scene quadrilaterals. First, we generalize a single line camera by removing the centering constraint that the principal axis should bisect a scene line. Then, we couple a pair of generalized line cameras to model a frustum with a quadrilateral base. Finally, we show that the scene quadrilateral and the center of projection can be analytically reconstructed from a single view when prior knowledge on the quadrilateral is available. A completely unknown quadrilateral can be reconstructed from four views through non-linear optimization. We also describe a improved method to handle an off-centered case by geometrically inferring a centered proxy quadrilateral, which accelerates a reconstruction process without relying on homography. The proposed method is easy to implement since each step is expressed as a simple analytic equation. We present the experimental results on real and synthetic examples.
[Submitted Version]
Title: Generalized Coupled Line Cameras and Application in Quadrilateral Reconstruction
Abstract:
Coupled line camera (CLC) provides a geometric framework to derive an analytic solution to reconstruct an unknown scene rectangle and the relevant projective structure from a single image quadrilateral. We extend this approach as generalized coupled line camera (GCLC) to handle a scene quadrilateral. First, we generalize a single line camera by removing the centering constraint that the principal axis should bisect a scene line. Then, we couple a pair of generalized line cameras to model a frustum with a quadrilateral base. Finally, we show that the scene quadrilateral and the center of projection can be analytically reconstructed from a single view when prior knowledge on the quadrilateral is available. ...
Automatic rectification of perspective distortion from a single image using p...ijcsa
Perspective distortion occurs due to the perspective projection of 3D scene on a 2D surface. Correcting the distortion of a single image without losing any desired information is one of the challenging task in the field of Computer Vision. We consider the problem of estimating perspective distortion from a single still image of an unstructured environment and to make perspective correction which is both quantitatively accurate as well as visually pleasing. Corners are detected based on the orientation of the image. A method based on plane homography and transformation is used to make perspective correction. The algorithm infers frontier information directly from the images, without any reference objects or prior knowledge of the camera parameters. The frontiers are detected using geometric context based segmentation. The goal of this paper is to present a framework providing fully automatic and fast perspective correction.
Solving the Pose Ambiguity via a Simple Concentric Circle ConstraintDr. Amarjeet Singh
Estimating the pose of objects with circle feature from images is a basic and important question in computer vision
community. This paper is focused on the ambiguity problem in pose estimation of circle feature, and a new method is proposed based
on the concentric circle constraint. The pose of a single circle feature, in general, can be determined from its projection in the image
plane with a pre-calibrated camera. However, there are generally two possible sets of pose parameters. By introducing the concentric
circle constraint, interference from the false solution can be excluded. On the basis of element at infinity in projective geometry and
the Euclidean distance invariant, cases that concentric circles are coplanar and non-coplanar are discussed respectively. Experiments
on these two cases are performed to validate the proposed method.
Image segmentation Based on Chan-Vese Active Contours using Finite Difference...ijsrd.com
There are a lot of image segmentation techniques that try to differentiate between backgrounds and object pixels but many of them fail to discriminate between different objects that are close to each other, e.g. low contrast between foreground and background regions increase the difficulty for segmenting images. So we introduced the Chan-Vese active contours model for image segmentation to detect the objects in given image, which is built based on techniques of curve evolution and level set method. The Chan-Vese model is a special case of Mumford-Shah functional for segmentation and level sets. It differs from other active contour models in that it is not edge dependent, therefore it is more capable of detecting objects whose boundaries may not be defined by a gradient. Finally, we developed code in Matlab 7.8 for solving resulting Partial differential equation numerically by the finite differences schemes on pixel-by-pixel domain.
Fast Complex Gabor Wavelet Based Palmprint AuthenticationCSCJournals
A biometric system is a pattern recognition system that recognizes a person on the basis of the physiological or behavioural characteristics that the person possesses. There is increasing interest of researchers in the development of fast and accurate personal recognition systems. In this paper, Sliding window method is used to make the system fast by reducing the matching time. The reduction in computation time indirectly reduces the overall comparison time that makes the system fast. Here, 2-D Complex Gabor Wavelet method is used to extract features from palmprint. The extracted features are stored in a feature vector and matched by hamming distance similarity measurement using sliding window approach. Reduction of 74.12% and 90.32% in comparison time is achieved using Sliding window methods. The improvement in time and accuracy as indicated by experimental results makes a system rapid and accurate.
A new hybrid method for the segmentation of the brain mrissipij
The magnetic resonance imaging is a method which has undeniable qualities of contrast and tissue
characterization, presenting an interest in the follow-up of various pathologies such as the multiple
sclerosis. In this work, a new method of hybrid segmentation is presented and applied to Brain MRIs. The
extraction of the image of the brain is pretreated with the Non Local Means filter. A theoretical approach is
proposed; finally the last section is organized around an experimental part allowing the study of the
behavior of our model on textured images. In the aim to validate our model, different segmentations were
down on pathological Brain MRI, the obtained results have been compared to the results obtained by
another models. This results show the effectiveness and the robustness of the suggested approach.
STUDY ANALYSIS ON TEETH SEGMENTATION USING LEVEL SET METHODaciijournal
The three dimensional shape information of teeth from cone beam computed tomography images provides
important assistance for dentist performing implant treatment, orthodontic surgery. This paper describes
the tooth root of both anterior and posterior teeth from CBCT images of head. The segmentation is done
using level set method with five energy functions. The edge energy used to move the curve towards border
of the object. The shape prior energy provides the shape of the contour. The dentine wall energy provides
interaction between the neighboring teeth and prevent shrinkage and leakage problem. The test result for
both segmentation and 3D reconstruction shows that the method can visualize both anterior and posterior
teeth with high accuracy and efficiency.
Nose Tip Detection Using Shape index and Energy Effective for 3d Face Recogni...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Comparative analysis and implementation of structured edge active contour IJECEIAES
This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image. In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared. It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.
M ESH S IMPLIFICATION V IA A V OLUME C OST M EASUREijcga
We develop a polygonal mesh simplification algorithm based on a novel analysis of the mesh
geometry.
Particularly, we propose first a characterization of vertices as hyperbolic or non
-
hyperbolic depend
-
ing
upon their discrete local geometry. Subsequently, the simplification process computes a volume cost for
each non
-
hyperbolic vertex, in anal
-
ogy with spherical volume, to capture the loss of fidelity if that vertex
is decimated. Vertices of least volume cost are then successively deleted and the resulting holes re
-
triangulated using a method based on a novel heuristic. Preliminary experiments i
ndicate a performance
comparable to that of the best known mesh simplification algorithms
Unimodal Multi-Feature Fusion and one-dimensional Hidden Markov Models for Lo...IJECEIAES
The objective of low-resolution face recognition is to identify faces from small size or poor quality images with varying pose, illumination, expression, etc. In this work, we propose a robust low face recognition technique based on one-dimensional Hidden Markov Models. Features of each facial image are extracted using three steps: firstly, both Gabor filters and Histogram of Oriented Gradients (HOG) descriptor are calculated. Secondly, the size of these features is reduced using the Linear Discriminant Analysis (LDA) method in order to remove redundant information. Finally, the reduced features are combined using Canonical Correlation Analysis (CCA) method. Unlike existing techniques using HMMs, in which authors consider each state to represent one facial region (eyes, nose, mouth, etc), the proposed system employs 1D-HMMs without any prior knowledge about the localization of interest regions in the facial image. Performance of the proposed method will be measured using the AR database.
IMPROVEMENTS OF THE ANALYSIS OF HUMAN ACTIVITY USING ACCELERATION RECORD OF E...sipij
The use of Holter Electrocardiograph (Holter ECG) is rapidly spreading. It is a wearableelectrocardiograph that records 24-hour electrocardiograms in a built-in flash memory, making it possibleto detect atrial fibrillation (Atrial Fibrillation, AF) through all-day activities. It is also useful for screeningfor diseases other than atrial fibrillation and for improving health. It is said that more useful informationcan be obtained by combining electrocardiograph with the analysis of physical activity. For that purpose,the Holter electrocardiograph is equipped with heart rate sensor and acceleration sensors. If accelerationdata is analysed, we can estimate activities in daily life, such as getting up, eating, walking, usingtransportation, and sitting. In combination with such activity status, electrocardiographic data can be expected to be more useful.
Java3D is an Application Programming Interface used for writing 3D graphics applications and applets. This paper gives a short introduction of java3D, analyses the mathematics of Hermite, Bezier, FourPoints, B-Splines curve, and describes implementation of curve creation and curve
operations using Java3D API.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations
involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
Dynamic texture based traffic vehicle monitoring systemeSAT Journals
Abstract Dynamic Textures are function of both space and time which exhibit spatio-temporal stationary property. They have spatially repetitive patterns which vary with time. In this paper, importance of phase spectrum in the signals is utilized and a novel method for vehicle monitoring is proposed with the help of Fourier analysis, synthesis and image processing. Methods like Doppler radar or GPS navigation are used commonly for tracking. The proposed image based approach has an added advantage that the clear image of the object (vehicle) can be used for future reference like proof of incidence, identification of owner and registration number. Keywords-Fourier Transform, dynamic texture, phase spectrum
Image restoration based on morphological operationsijcseit
Image processing including noise suppression, feature extraction, edge detection, image segmentation,
shape recognition, texture analysis, image restoration and reconstruction, image compression etc uses
mathematical morphology which is a method of nonlinear filters.
It is modulated from traditional morphology to order morphology, soft mathematical morphology and fuzzy
soft mathematical morphology. This paper is covers 6 morphological operations which are implemented in
the matlab program, including erosion, dilation, opening, closing, boundary extraction and region filling.
A Numerical Method for Modelling Discontinuous Mechanics of Asphalt MixtureIDES Editor
In order to simulate discontinuous mechanics for
asphalt mixture pavement, a new numerical scheme—
Meshfree Manifold Method is deduced in this paper by
integrating Numerical Manifold Method and Mesh-free
Method, which is not only appropriate for contact computation
but easy to eliminate the limitation of regular mesh. Some
kernel principles are discussedÿand an example is given to
prove its efficiency in simulating discontinuous deformation
of asphalt mixture.
The predominant technology that is used by CAD (Com- puter Aided Design) to represent complex geometries is non-uniform rational b-splines (NURBS). This allows cer- tain geometries to be represented exactly including conic and circular sections. There is a vast array of literature focused on NURBS and as a result of several decades f research, many efficient computer algorithms exist for their fast evaluation and refinement. The key concept outlined by Hughes et al. was to employ NURBS not only as a geometry discretisation technology, but also as a discretisation tool for analysis, attributing such methods to the field of ‘isogeometric analysis’ (IGA).
Hybrid medical image compression method using quincunx wavelet and geometric ...journalBEEI
The purpose of this article is to find an efficient and optimal method of compression by reducing the file size while retaining the information for a good quality processing and to produce credible pathological reports, based on the extraction of the information characteristics contained in medical images. In this article, we proposed a novel medical image compression that combines geometric active contour model and quincunx wavelet transform. In this method it is necessary to localize the region of interest, where we tried to localize all the part that contain the pathological, using the level set for an optimal reduction, then we use the quincunx wavelet coupled with the set partitioning in hierarchical trees (SPIHT) algorithm. After testing several algorithms we noticed that the proposed method gives satisfactory results. The comparison of the experimental results is based on parameters of evaluation.
SURVEY ON POLYGONAL APPROXIMATION TECHNIQUES FOR DIGITAL PLANAR CURVESZac Darcy
Polygon approximation plays a vital role in abquitious applications like multimedia, geographic and object
recognition. An extensive number of polygonal approximation techniques for digital planar curves have
been proposed over the last decade, but there are no survey papers on recently proposed techniques.
Polygon is a collection of edges and vertices. Objects are represented using edges and vertices or contour
points (ie. polygon). Polygonal approximation is representing the object with less number of dominant
points (less number of edges and vertices). Polygon approximation results in less computational speed and
memory usage. This paper deals with comparative study on polygonal approximation techniques for digital
planar curves with respect to their computation and efficiency.
Application of parallel algorithm approach for performance optimization of oi...sipij
This paper gives a detailed study on the performance of image filter algorithm with various parameters
applied on an image of RGB model. There are various popular image filters, which consumes large amount
of computing resources for processing. Oil paint image filter is one of the very interesting filters, which is
very performance hungry. Current research tries to find improvement in oil paint image filter algorithm by
using parallel pattern library. With increasing kernel-size, the processing time of oil paint image filter
algorithm increases exponentially. I have also observed in various blogs and forums, the questions for
faster oil paint have been asked repeatedly.
Parallax Effect Free Mosaicing of Underwater Video Sequence Based on Texture ...sipij
In this paper, we present feature-based technique for construction of mosaic image from underwater video
sequence, which suffers from parallax distortion due to propagation properties of light in the underwater
environment. The most of the available mosaic tools and underwater image mosaicing techniques yields
final result with some artifacts such as blurring, ghosting and seam due to presence of parallax in the input
images. The removal of parallax from input images may not reduce its effects instead it must be corrected
in successive steps of mosaicing. Thus, our approach minimizes the parallax effects by adopting an efficient
local alignment technique after global registration. We extract texture features using Centre Symmetric
Local Binary Pattern (CS-LBP) descriptor in order to find feature correspondences, which are used further
for estimation of homography through RANSAC. In order to increase the accuracy of global registration,
we perform preprocessing such as colour alignment between two selected frames based on colour
distribution adjustment. Because of existence of 100% overlap in consecutive frames of underwater video,
we select frames with minimum overlap based on mutual offset in order to reduce the computation cost
during mosaicing. Our approach minimizes the parallax effects considerably in final mosaic constructed
using our own underwater video sequences.
IDENTIFICATION OF SUITED QUALITY METRICS FOR NATURAL AND MEDICAL IMAGESsipij
To assess quality of the denoised image is one of the important task in image denoising application.
Numerous quality metrics are proposed by researchers with their particular characteristics till today. In
practice, image acquisition system is different for natural and medical images. Hence noise introduced in
these images is also different in nature. Considering this fact, authors in this paper tried to identify the
suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images
respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with
respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to
develop noise dependent quality metric is also identified in this work.
STUDY ANALYSIS ON TEETH SEGMENTATION USING LEVEL SET METHODaciijournal
The three dimensional shape information of teeth from cone beam computed tomography images provides
important assistance for dentist performing implant treatment, orthodontic surgery. This paper describes
the tooth root of both anterior and posterior teeth from CBCT images of head. The segmentation is done
using level set method with five energy functions. The edge energy used to move the curve towards border
of the object. The shape prior energy provides the shape of the contour. The dentine wall energy provides
interaction between the neighboring teeth and prevent shrinkage and leakage problem. The test result for
both segmentation and 3D reconstruction shows that the method can visualize both anterior and posterior
teeth with high accuracy and efficiency.
Nose Tip Detection Using Shape index and Energy Effective for 3d Face Recogni...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Comparative analysis and implementation of structured edge active contour IJECEIAES
This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image. In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared. It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.
M ESH S IMPLIFICATION V IA A V OLUME C OST M EASUREijcga
We develop a polygonal mesh simplification algorithm based on a novel analysis of the mesh
geometry.
Particularly, we propose first a characterization of vertices as hyperbolic or non
-
hyperbolic depend
-
ing
upon their discrete local geometry. Subsequently, the simplification process computes a volume cost for
each non
-
hyperbolic vertex, in anal
-
ogy with spherical volume, to capture the loss of fidelity if that vertex
is decimated. Vertices of least volume cost are then successively deleted and the resulting holes re
-
triangulated using a method based on a novel heuristic. Preliminary experiments i
ndicate a performance
comparable to that of the best known mesh simplification algorithms
Unimodal Multi-Feature Fusion and one-dimensional Hidden Markov Models for Lo...IJECEIAES
The objective of low-resolution face recognition is to identify faces from small size or poor quality images with varying pose, illumination, expression, etc. In this work, we propose a robust low face recognition technique based on one-dimensional Hidden Markov Models. Features of each facial image are extracted using three steps: firstly, both Gabor filters and Histogram of Oriented Gradients (HOG) descriptor are calculated. Secondly, the size of these features is reduced using the Linear Discriminant Analysis (LDA) method in order to remove redundant information. Finally, the reduced features are combined using Canonical Correlation Analysis (CCA) method. Unlike existing techniques using HMMs, in which authors consider each state to represent one facial region (eyes, nose, mouth, etc), the proposed system employs 1D-HMMs without any prior knowledge about the localization of interest regions in the facial image. Performance of the proposed method will be measured using the AR database.
IMPROVEMENTS OF THE ANALYSIS OF HUMAN ACTIVITY USING ACCELERATION RECORD OF E...sipij
The use of Holter Electrocardiograph (Holter ECG) is rapidly spreading. It is a wearableelectrocardiograph that records 24-hour electrocardiograms in a built-in flash memory, making it possibleto detect atrial fibrillation (Atrial Fibrillation, AF) through all-day activities. It is also useful for screeningfor diseases other than atrial fibrillation and for improving health. It is said that more useful informationcan be obtained by combining electrocardiograph with the analysis of physical activity. For that purpose,the Holter electrocardiograph is equipped with heart rate sensor and acceleration sensors. If accelerationdata is analysed, we can estimate activities in daily life, such as getting up, eating, walking, usingtransportation, and sitting. In combination with such activity status, electrocardiographic data can be expected to be more useful.
Java3D is an Application Programming Interface used for writing 3D graphics applications and applets. This paper gives a short introduction of java3D, analyses the mathematics of Hermite, Bezier, FourPoints, B-Splines curve, and describes implementation of curve creation and curve
operations using Java3D API.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations
involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
Dynamic texture based traffic vehicle monitoring systemeSAT Journals
Abstract Dynamic Textures are function of both space and time which exhibit spatio-temporal stationary property. They have spatially repetitive patterns which vary with time. In this paper, importance of phase spectrum in the signals is utilized and a novel method for vehicle monitoring is proposed with the help of Fourier analysis, synthesis and image processing. Methods like Doppler radar or GPS navigation are used commonly for tracking. The proposed image based approach has an added advantage that the clear image of the object (vehicle) can be used for future reference like proof of incidence, identification of owner and registration number. Keywords-Fourier Transform, dynamic texture, phase spectrum
Image restoration based on morphological operationsijcseit
Image processing including noise suppression, feature extraction, edge detection, image segmentation,
shape recognition, texture analysis, image restoration and reconstruction, image compression etc uses
mathematical morphology which is a method of nonlinear filters.
It is modulated from traditional morphology to order morphology, soft mathematical morphology and fuzzy
soft mathematical morphology. This paper is covers 6 morphological operations which are implemented in
the matlab program, including erosion, dilation, opening, closing, boundary extraction and region filling.
A Numerical Method for Modelling Discontinuous Mechanics of Asphalt MixtureIDES Editor
In order to simulate discontinuous mechanics for
asphalt mixture pavement, a new numerical scheme—
Meshfree Manifold Method is deduced in this paper by
integrating Numerical Manifold Method and Mesh-free
Method, which is not only appropriate for contact computation
but easy to eliminate the limitation of regular mesh. Some
kernel principles are discussedÿand an example is given to
prove its efficiency in simulating discontinuous deformation
of asphalt mixture.
The predominant technology that is used by CAD (Com- puter Aided Design) to represent complex geometries is non-uniform rational b-splines (NURBS). This allows cer- tain geometries to be represented exactly including conic and circular sections. There is a vast array of literature focused on NURBS and as a result of several decades f research, many efficient computer algorithms exist for their fast evaluation and refinement. The key concept outlined by Hughes et al. was to employ NURBS not only as a geometry discretisation technology, but also as a discretisation tool for analysis, attributing such methods to the field of ‘isogeometric analysis’ (IGA).
Hybrid medical image compression method using quincunx wavelet and geometric ...journalBEEI
The purpose of this article is to find an efficient and optimal method of compression by reducing the file size while retaining the information for a good quality processing and to produce credible pathological reports, based on the extraction of the information characteristics contained in medical images. In this article, we proposed a novel medical image compression that combines geometric active contour model and quincunx wavelet transform. In this method it is necessary to localize the region of interest, where we tried to localize all the part that contain the pathological, using the level set for an optimal reduction, then we use the quincunx wavelet coupled with the set partitioning in hierarchical trees (SPIHT) algorithm. After testing several algorithms we noticed that the proposed method gives satisfactory results. The comparison of the experimental results is based on parameters of evaluation.
SURVEY ON POLYGONAL APPROXIMATION TECHNIQUES FOR DIGITAL PLANAR CURVESZac Darcy
Polygon approximation plays a vital role in abquitious applications like multimedia, geographic and object
recognition. An extensive number of polygonal approximation techniques for digital planar curves have
been proposed over the last decade, but there are no survey papers on recently proposed techniques.
Polygon is a collection of edges and vertices. Objects are represented using edges and vertices or contour
points (ie. polygon). Polygonal approximation is representing the object with less number of dominant
points (less number of edges and vertices). Polygon approximation results in less computational speed and
memory usage. This paper deals with comparative study on polygonal approximation techniques for digital
planar curves with respect to their computation and efficiency.
Application of parallel algorithm approach for performance optimization of oi...sipij
This paper gives a detailed study on the performance of image filter algorithm with various parameters
applied on an image of RGB model. There are various popular image filters, which consumes large amount
of computing resources for processing. Oil paint image filter is one of the very interesting filters, which is
very performance hungry. Current research tries to find improvement in oil paint image filter algorithm by
using parallel pattern library. With increasing kernel-size, the processing time of oil paint image filter
algorithm increases exponentially. I have also observed in various blogs and forums, the questions for
faster oil paint have been asked repeatedly.
Parallax Effect Free Mosaicing of Underwater Video Sequence Based on Texture ...sipij
In this paper, we present feature-based technique for construction of mosaic image from underwater video
sequence, which suffers from parallax distortion due to propagation properties of light in the underwater
environment. The most of the available mosaic tools and underwater image mosaicing techniques yields
final result with some artifacts such as blurring, ghosting and seam due to presence of parallax in the input
images. The removal of parallax from input images may not reduce its effects instead it must be corrected
in successive steps of mosaicing. Thus, our approach minimizes the parallax effects by adopting an efficient
local alignment technique after global registration. We extract texture features using Centre Symmetric
Local Binary Pattern (CS-LBP) descriptor in order to find feature correspondences, which are used further
for estimation of homography through RANSAC. In order to increase the accuracy of global registration,
we perform preprocessing such as colour alignment between two selected frames based on colour
distribution adjustment. Because of existence of 100% overlap in consecutive frames of underwater video,
we select frames with minimum overlap based on mutual offset in order to reduce the computation cost
during mosaicing. Our approach minimizes the parallax effects considerably in final mosaic constructed
using our own underwater video sequences.
IDENTIFICATION OF SUITED QUALITY METRICS FOR NATURAL AND MEDICAL IMAGESsipij
To assess quality of the denoised image is one of the important task in image denoising application.
Numerous quality metrics are proposed by researchers with their particular characteristics till today. In
practice, image acquisition system is different for natural and medical images. Hence noise introduced in
these images is also different in nature. Considering this fact, authors in this paper tried to identify the
suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images
respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with
respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to
develop noise dependent quality metric is also identified in this work.
A voting based approach to detect recursive order number of photocopy documen...sipij
Photocopy documents are very common in our normal life. People are permitted to carry and present
photocopied documents to avoid damages to the original documents. But this provision is misused for
temporary benefits by fabricating fake photocopied documents. Fabrication of fake photocopied document
is possible only in 2nd and higher order recursive order of photocopies. Whenever a photocopied document
is submitted, it may be required to check its originality. When the document is 1st order photocopy, chances
of fabrication may be ignored. On the other hand when the photocopy order is 2nd or above, probability of
fabrication may be suspected. Hence when a photocopy document is presented, the recursive order number
of photocopy is to be estimated to ascertain the originality. This requirement demands to investigate
methods to estimate order number of photocopy. In this work, a voting based approach is used to detect the
recursive order number of the photocopy document using probability distributions exponential, extreme
values and lognormal distributions is proposed. A detailed experimentation is performed on a generated
data set and the method exhibits efficiency close to 89%.
A combined method of fractal and glcm features for mri and ct scan images cla...sipij
Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale
complexity. The fractal feature is a compact descriptor used to give a numerical measure of the degree of
irregularity of the medical images. This descriptor property does not give ownership of the local image
structure. In this paper, we present a combination of this parameter based on Box Counting with GLCM
Features. This powerful combination has proved good results especially in classification of medical texture
from MRI and CT Scan images of trabecular bone. This method has the potential to improve clinical
diagnostics tests for osteoporosis pathologies.
Review of ocr techniques used in automatic mail sorting of postal envelopessipij
This paper presents a review of various OCR techniq
ues used in the automatic mail sorting process. A
complete description on various existing methods fo
r address block extraction and digit recognition th
at
were used in the literature is discussed. The objec
tive of this study is to provide a complete overvie
w about
the methods and techniques used by many researchers
for automating the mail sorting process in postal
service in various countries. The significance of Z
ip code or Pincode recognition is discussed.
Feature selection approach in animal classificationsipij
In this paper, we propose a model for automatic classification of Animals using different classifiers Nearest
Neighbour, Probabilistic Neural Network and Symbolic. Animal images are segmented using maximal
region merging segmentation. The Gabor features are extracted from segmented animal images.
Discriminative texture features are then selected using the different feature selection algorithm like
Sequential Forward Selection, Sequential Floating Forward Selection, Sequential Backward Selection and
Sequential Floating Backward Selection. To corroborate the efficacy of the proposed method, an
experiment was conducted on our own data set of 25 classes of animals, containing 2500 samples. The
data set has different animal species with similar appearance (small inter-class variations) across different
classes and varying appearance (large intra-class variations) within a class. In addition, the images of
flowers are of different poses, with cluttered background under different lighting and climatic conditions.
Experiment results reveal that Symbolic classifier outperforms Nearest Neighbour and Probabilistic Neural
Network classifiers.
Image retrieval and re ranking techniques - a surveysipij
There is a huge amount of research work focusing on the searching, retrieval and re-ranking of images in
the image database. The diverse and scattered work in this domain needs to be collected and organized for
easy and quick reference.
Relating to the above context, this paper gives a brief overview of various image retrieval and re-ranking
techniques. Starting with the introduction to existing system the paper proceeds through the core
architecture of image harvesting and retrieval system to the different Re-ranking techniques. These
techniques are discussed in terms of approaches, methodologies and findings and are listed in tabular form
for quick review.
An intensity based medical image registration using genetic algorithmsipij
Medical imaging plays a vital role to create images of human body for clinical purposes. Biomedical
imaging has taken a leap by entering into the field of image registration. Image registration integrates the
large amount of medical information embedded in the images taken at different time intervals and images
at different orientations. In this paper, an intensity-based real-coded genetic algorithm is used for
registering two MRI images. To demonstrate the efficiency of the algorithm developed, the alignment of the
image is altered and algorithm is tested for better performance. Also the work involves the comparison of
two similarity metrics, and based on the outcome the best metric suited for genetic algorithm is studied.
Contrast enhancement using various statistical operations and neighborhood pr...sipij
Histogram Equalization is a simple and effective contrast enhancement technique. In spite of its popularity
Histogram Equalization still have some limitations –produces artifacts, unnatural images and the local
details are not considered, therefore due to these limitations many other Equalization techniques have been
derived from it with some up gradation. In this proposed method statistics play an important role in image
processing, where statistical operations is applied to the image to get the desired result such as
manipulation of brightness and contrast. Thus, a novel algorithm using statistical operations and
neighborhood processing has been proposed in this paper where the algorithm has proven to be effective in
contrast enhancement based on the theory and experiment.
Lossless image compression using new biorthogonal waveletssipij
Even though a large number of wavelets exist, one needs new wavelets for their specific applications. One
of the basic wavelet categories is orthogonal wavelets. But it was hard to find orthogonal and symmetric
wavelets. Symmetricity is required for perfect reconstruction. Hence, a need for orthogonal and symmetric
arises. The solution was in the form of biorthogonal wavelets which preserves perfect reconstruction
condition. Though a number of biorthogonal wavelets are proposed in the literature, in this paper four new
biorthogonal wavelets are proposed which gives better compression performance. The new wavelets are
compared with traditional wavelets by using the design metrics Peak Signal to Noise Ratio (PSNR) and
Compression Ratio (CR). Set Partitioning in Hierarchical Trees (SPIHT) coding algorithm was utilized to
incorporate compression of images.
Beamforming with per antenna power constraint and transmit antenna selection ...sipij
In this paper, transmit beamforming and antenna selection techniques are presented for the Cooperative
Distributed Antenna System. Beamforming technique with minimum total weighted transmit power
satisfying threshold SINR and Per-Antenna Power constraints is formulated as a convex optimization
problem for the efficient performance of Distributed Antenna System (DAS). Antenna Selection technique is
implemented in this paper to select the optimum Remote Antenna Units from all the available ones. This
achieves the best compromise between capacity and system complexity. Dual polarized and Triple
Polarized systems are considered. Simulation results prove that by integrating Beamforming with DAS
enhances its performance. Also by using convex optimization in Antenna Selection enhances the
performance of multi polarized systems.
A Novel Uncertainty Parameter SR ( Signal to Residual Spectrum Ratio ) Evalua...sipij
Usually, hearing impaired people use hearing aids which are implemented with speech enhancement
algorithms. Estimation of speech and estimation of nose are the components in single channel speech
enhancement system. The main objective of any speech enhancement algorithm is estimation of noise power
spectrum for non stationary environment. VAD (Voice Activity Detector) is used to identify speech pauses
and during these pauses only estimation of noise. MMSE (Minimum Mean Square Error) speech
enhancement algorithm did not enhance the intelligibility, quality and listener fatigues are the perceptual
aspects of speech. Novel evaluation approach SR (Signal to Residual spectrum ratio) based on uncertainty
parameter introduced for the benefits of hearing impaired people in non stationary environments to control
distortions. By estimation and updating of noise based on division of original pure signal into three parts
such as pure speech, quasi speech and non speech frames based on multiple threshold conditions. Different
values of SR and LLR demonstrate the amount of attenuation and amplification distortions. The proposed
method will compared with any one method WAT(Weighted Average Technique) Hence by using
parameters SR (signal to residual spectrum ratio) and LLR (log like hood ratio), MMSE (Minim Mean
Square Error) in terms of segmented SNR and LLR.
Robust content based watermarking algorithm using singular value decompositio...sipij
Nowadays, image content is frequently subject to different malicious manipulations. To protect images
from this illegal manipulations computer science community have recourse to watermarking techniques. To
protect digital multimedia content we need just to embed an invisible watermark into images which
facilitate the detection of different manipulations, duplication, illegitimate distributions of these images. In
this work a robust watermarking technique is presented that embedding invisible watermarks into colour
images the singular value decomposition bloc by bloc of a robust transform of images that is the Radial
symmetry transform. Each bit of the watermark is inserted in a bloc of eight pixels large of the blue
channel a high singular value of the corresponding bloc into the radial symmetry map. We justified the
insertion in the blue channel by our feeble sensibility to perturbations in this colour channel of images. We
present also results obtained with different tests. We had tested the imperceptibility of the mark using this
approach and also its robustness face to several attacks.
Speaker Identification From Youtube Obtained Datasipij
An efficient, and intuitive algorithm is presented for the identification of speakers from a long dataset (like
YouTube long discussion, Cocktail party recorded audio or video).The goal of automatic speaker
identification is to identify the number of different speakers and prepare a model for that speaker by
extraction, characterization and speaker-specific information contained in the speech signal. It has many
diverse application specially in the field of Surveillance , Immigrations at Airport , cyber security ,
transcription in multi-source of similar sound source, where it is difficult to assign transcription arbitrary.
The most commonly speech parameterization used in speaker verification, K-mean, cepstral analysis, is
detailed. Gaussian mixture modeling, which is the speaker modeling technique is then explained. Gaussian
mixture models (GMM), perhaps the most robust machine learning algorithm has been introduced to
examine and judge carefully speaker identification in text independent. The application or employment of
Gaussian mixture models for monitoring & Analysing speaker identity is encouraged by the familiarity,
awareness, or understanding gained through experience that Gaussian spectrum depict the characteristics
of speaker's spectral conformational pattern and remarkable ability of GMM to construct capricious
densities after that we illustrate 'Expectation maximization' an iterative algorithm which takes some
arbitrary value in initial estimation and carry on the iterative process until the convergence of value is
observed We have tried to obtained 85 ~ 95% of accuracy using speaker modeling of vector quantization
and Gaussian Mixture model ,so by doing various number of experiments we are able to obtain 79 ~ 82%
of identification rate using Vector quantization and 85 ~ 92.6% of identification rate using GMM modeling
by Expectation maximization parameter estimation depending on variation of parameter.
Offline handwritten signature identification using adaptive window positionin...sipij
The paper presents to address this challenge, we have proposed the use of Adaptive Window Positioning
technique which focuses on not just the meaning of the handwritten signature but also on the individuality
of the writer. This innovative technique divides the handwritten signature into 13 small windows of size nxn
(13x13). This size should be large enough to contain ample information about the style of the author and
small enough to ensure a good identification performance. The process was tested with a GPDS dataset
containing 4870 signature samples from 90 different writers by comparing the robust features of the test
signature with that of the user’s signature using an appropriate classifier. Experimental results reveal that
adaptive window positioning technique proved to be the efficient and reliable method for accurate
signature feature extraction for the identification of offline handwritten signatures .The contribution of this
technique can be used to detect signatures signed under emotional duress
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
ROLE OF HYBRID LEVEL SET IN FETAL CONTOUR EXTRACTIONsipij
Image processing technologies may be employed for quicker and accurate diagnosis in analysis and
feature extraction of medical images. Here, existing level set algorithm is modified and it is employed for
extracting contour of fetus in an image. In traditional approach, fetal parameters are extracted manually
from ultrasound images. An automatic technique is highly desirable to obtain fetal biometric measurements
due to some problems in traditional approach such as lack of consistency and accuracy. The proposed
approach utilizes global & local region information for fetal contour extraction from ultrasonic images.
The main goal of this research is to develop a new methodology to aid the analysis and feature extraction.
Role of Hybrid Level Set in Fetal Contour Extractionsipij
Image processing technologies may be employed for quicker and accurate diagnosis in analysis and
feature extraction of medical images. Here, existing level set algorithm is modified and it is employed for
extracting contour of fetus in an image. In traditional approach, fetal parameters are extracted manually
from ultrasound images. An automatic technique is highly desirable to obtain fetal biometric measurements
due to some problems in traditional approach such as lack of consistency and accuracy. The proposed
approach utilizes global & local region information for fetal contour extraction from ultrasonic images.
The main goal of this research is to develop a new methodology to aid the analysis and feature extraction.
Copy-Rotate-Move Forgery Detection Based on Spatial DomainSondosFadl
we propose a method which is efficient and fast for detecting Copy-Move regions even when the copied region was undergone rotation modify in spatial domain.
Performance Comparison of PCA,DWT-PCA And LWT-PCA for Face Image RetrievalCSEIJJournal
This paper compares the performance of face image retrieval system based on discrete wavelet transforms
and Lifting wavelet transforms with principal component analysis (PCA). These techniques are
implemented and their performances are investigated using frontal facial images from the ORL database.
The Discrete Wavelet Transform is effective in representing image features and is suitable in Face image
retrieval, it still encounters problems especially in implementation; e.g. Floating point operation and
decomposition speed. We use the advantages of lifting scheme, a spatial approach for constructing wavelet
filters, which provides feasible alternative for problems facing its classical counterpart. Lifting scheme has
such intriguing properties as convenient construction, simple structure, integer-to-integer transform, low
computational complexity as well as flexible adaptivity, revealing its potentials in Face image retrieval.
Comparing to PCA and DWT with PCA, Lifting wavelet transform with PCA gives less computation and
DWT-PCA gives high retrieval rate..
Performance Comparison of PCA,DWT-PCA And LWT-PCA for Face Image RetrievalCSEIJJournal
This paper compares the performance of face image retrieval system based on discrete wavelet transforms
and Lifting wavelet transforms with principal component analysis (PCA). These techniques are
implemented and their performances are investigated using frontal facial images from the ORL database.
The Discrete Wavelet Transform is effective in representing image features and is suitable in Face image
retrieval, it still encounters problems especially in implementation; e.g. Floating point operation and
decomposition speed. We use the advantages of lifting scheme, a spatial approach for constructing wavelet
filters, which provides feasible alternative for problems facing its classical counterpart. Lifting scheme has
such intriguing properties as convenient construction, simple structure, integer-to-integer transform, low
computational complexity as well as flexible adaptivity, revealing its potentials in Face image retrieval.
Comparing to PCA and DWT with PCA, Lifting wavelet transform with PCA gives less computation and
DWT-PCA gives high retrieval rate..
Edge Extraction with an Anisotropic Vector Field using Divergence MapCSCJournals
The aim of this work is the extraction of edges by a deformable contour procedure, using an external force field derived from an anisotropic flow, with different external and initial conditions. By evaluating the divergence of the force field, we have generated a divergence map associated with it in order to analyze the field convergence. As we know, the divergence measures the intensity of convergence or divergence of a vector field at a given point, so by means level curves of the divergence map, we have automatically selected an initial contour for the deformation process. The initial curve must include areas from which the vector field diverges pushing it towards the edges. Furthermore the divergence map brings out the presence of curves pointing to the most significant geometric parts of boundaries corresponding to high curvature values, in this way it will result better defined the geometrical shape of the extracted object.
External Force for Deformable Models in Medical Image Segmentation: A Surveysipij
Many image segmentation techniques are available in the literature. Among the available techniques, parametric deformable models play an important role in many medical imaging applications. These models have been proved to be effective in segmenting an anatomic structure using constraints derived from the image data along with a prior knowledge about the location, size and shape of these structures. These models also support highly intuitive interaction mechanisms, which helps medical practitioners to bring their expertise to bear on the model-based image interpretation task. In this paper, a review of nineteen different external forces for the parametric deformable model applied to the medical image segmentation is presented. The main purpose of survey is to identify and discuss each category with its principle, mathematical model, advantages, disadvantages and applications to medical image analysis.
Face recognition based on curvelets, invariant moments features and SVMTELKOMNIKA JOURNAL
Recent studies highlighted on face recognition methods. In this paper, a new algorithm is proposed for face recognition by combining Fast Discrete Curvelet Transform (FDCvT) and Invariant Moments with Support vector machine (SVM), which improves rate of face recognition in various situations. The reason of using this approach depends on two things. first, Curvelet transform which is a multi-resolution method, that can efficiently represent image edge discontinuities; Second, the Invariant Moments analysis which is a statistical method that meets with the translation, rotation and scale invariance in the image. Furthermore, SVM is employed to classify the face image based on the extracted features. This process is applied on each of ORL and Yale databases to evaluate the performance of the suggested method. Experimentally, the proposed method results show that our system can compose efficient and reasonable face recognition feature, and obtain useful recognition accuracy, which is able to face and side-face states detection of persons to decrease fault rate of production.
Using Generic Image Processing Operations to Detect a Calibration GridJan Wedekind
Camera calibration is an important problem in 3D computer vision. The problem of determining the camera parameters has been studied extensively. However the algorithms for determining the required correspondences are either semi-automatic (i.e. they require user interaction) or they involve difficult to implement custom algorithms.
We present a robust algorithm for detecting the corners of a calibration grid and assigning the correct correspondences for calibration . The solution is based on generic image processing operations so that it can be implemented quickly. The algorithm is limited to distortion-free cameras but it could potentially be extended to deal with camera distortion as well. We also present a corner detector based on steerable filters. The corner detector is particularly suited for the problem of detecting the corners of a calibration grid.
- See more at: http://figshare.com/articles/Using_Generic_Image_Processing_Operations_to_Detect_a_Calibration_Grid/696880#sthash.EG8dWyTH.dpuf
A Hybrid Technique for the Automated Segmentation of Corpus Callosum in Midsa...IJERA Editor
The corpus callosum (CC) is the largest white-matter structure in human brain. In this paper, we take two techniques to observe the results of segmentation of Corpus Callosum. The first one is mean shift algorithm and morphological operation. The second one is k-means clustering. In this paper, it is performed in three steps. The first step is finding the corpus callosum area using adaptive mean shift algorithm or k-means clustering . In second step, the boundary of detected CC area is then used as the initial contour in the Geometric Active Contour (GAC) mode and final step to remove unknown noise using morphological operation and evolved to get the final segmentation result. The experimental results demonstrate that the mean shift algorithm and k-means clustering has provided a reliable segmentation performance.
Boosting ced using robust orientation estimationijma
In this paper, Coherence Enhancement Diffusion (CED) is boosted feeding external orientation using new
robust orientation estimation. In CED, proper scale selection is very important as the gradient vector at
that scale reflects the orientation of local ridge. For this purpose a new scheme is proposed in which pre
calculated orientation, by using local and integration scales. From the experiments it is found the proposed
scheme is working much better in noisy environment as compared to the traditional Coherence
Enhancement Diffusion
ANALYSIS OF INTEREST POINTS OF CURVELET COEFFICIENTS CONTRIBUTIONS OF MICROS...sipij
This paper focuses on improved edge model based on Curvelet coefficients analysis. Curvelet transform is
a powerful tool for multiresolution representation of object with anisotropic edge. Curvelet coefficients
contributions have been analyzed using Scale Invariant Feature Transform (SIFT), commonly used to study
local structure in images. The permutation of Curvelet coefficients from original image and edges image
obtained from gradient operator is used to improve original edges. Experimental results show that this
method brings out details on edges when the decomposition scale increases.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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Global threshold and region based active contour model for accurate image segmentation
1. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
DOI : 10.5121/sipij.2014.5301 1
GLOBAL THRESHOLD AND REGION-BASED
ACTIVE CONTOUR MODEL FOR ACCURATE
IMAGE SEGMENTATION
Nuseiba M. Altarawneh1
, Suhuai Luo1
, Brian Regan1
, Changming Sun2
,
Fucang Jia3
1
School of Design Communication and IT, the University of Newcastle,
Callaghan NSW 2308, Australia
2
CSIRO Computational Informatics, Locked Bag 17,
North Ryde, NSW 1670, Australia
3
Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen 518055, China
ABSTRACT
In this contribution, we develop a novel global threshold-based active contour model. This model deploys a new
edge-stopping function to control the direction of the evolution and to stop the evolving contour at weak or
blurred edges. An implementation of the model requires the use of selective binary and Gaussian filtering
regularized level set (SBGFRLS) method. The method uses either a selective local or global segmentation
property. It penalizes the level set function to force it to become a binary function. This procedure is followed by
using a regularisation Gaussian. The Gaussian filters smooth the level set function and stabilises the evolution
process. One of the merits of our proposed model stems from the ability to initialise the contour anywhere inside
the image to extract object boundaries. The proposed method is found to perform well, notably when the
intensities inside and outside the object are homogenous. Our method is applied with satisfactory results on
various types of images, including synthetic, medical and Arabic-characters images.
KEYWORDS
Active contour model, Level set method, CV model, ZAC model.
1. INTRODUCTION
Active contour model (ACM) signifies one of the most successful techniques in dealing
with image segmentation problems. The idea behind the ACM is to evolve a curve or a
surface defined within an image from some arbitrary initial shape towards its interior normal
direction and stop it on the object boundary [1]. The parametric curve is linked with an energy
function. During the deformation, the curve tries to minimize its energy so that the final curve
possesses a local minimum when the contour is spatially aligned with the shape or the desired
image features. Thus the problem of segmentation is reduced to an energy minimization
problem [2].
In order to locate the desired image features, parametric curves are initialized close to the
desired feature and are forced to move toward the local minimum that is located on the desired
features under the influence of internal and external forces. The internal forces are defined
within the curve or surface to keep the model smooth during the deformation. The external
2. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
2
forces are derived from the image data to move the curve toward the object boundary or the
desired features within an image.
Owing to its flexibility in allowing topological changes, the level set method has been
extensively utilized in problems such as curve evolution, especially the curve motion by mean
curvature as described by Osher and Sethian [3]. In the level set method, the evolution curve is
represented implicitly via a Lipchitz functionφ , as {( , ) | ( , ) =0}C x y x yφ= . The zero level set
of the function ( , , )t x yφ represents the evolution curve C at time t . The evolution of the
curve C in a normal direction with speed F is obtained by solving the equation:
where{( , ) | ( , ) =0}x y x yφ represents the initial contour. The geodesic active contour models
[4, 5] utilize the image gradient in order to construct an edge detector function. The objective
of this function is to stop the contour evolution on the object boundary. The general edge
detector function can be defined by a positive and decreasing function such as:
where 0u is a given image in Ω and 0*G uσ denotes a smooth version of 0u after convolving it
with the Gaussian function. The values of 0( )g u∇ function will be positive in the homogenous
regions and zero on the object boundary. A particular case is the motion by mean curvature in
which ( ( , )/ | ( , ) |)F div x y x yφ φ= ∇ ∇ . Malladi et al. [6] proposed the following level set
equation:
0
2
0
2
1 2
( ( * ))
( )
( , ,0) ( , ) in
v
v G u m
t m m
x y x y R
σ
φ
φ
φ φ
∂
= ∇ − + ∇ −
∂ +
= (3)
where v is a constant, and m1 and m2 are the maximum and minimum values of the image
gradient 0*G uσ∇ , respectively. The evolving curve stops at the boundary, i.e., points with
the highest gradient. Caselles et al. [5] proposed a Geometric Active Contour model (GAC)
based on the mean curvature motion:
where v is a constant. In GAC the curve moves in the normal direction with a speed equal to
(| |)( ( / | |) + )og u div vφ φ∇ ∇ ∇ . The curve will stop the evolution when the function g vanishes.
All the above ACMs are termed as edge-based models [7-10] because they utilize the image
gradient as stopping criterion for the evolving curve. Edge-based models do not perform well
in the presence of noise and in images with weak edges or without edges. In the case of a
discrete gradient, the curve may pass through the edges because the function 0( )g u∇ never
2
2
0
in [0, ]
( , ,0) ( , ) in (1)
F R
t
x y x y R
φ
φ
φ φ
∂
= ∇ ∞ ∈
∂
=
0
0
1
( ) (2)
1 ( , ) * ( , )
g u
G x y u x yσ
∇ =
+ ∇
2
0
2
0
(| ) | ( ( ) ) in [0, ]
( , ,0) ( , ) in (4)
g u div v R
t
x y x y R
φ φ
φ
φ
φ φ
∂ ∇
= ∇ ∇ + ∞ ∈ ∂ ∇
=
3. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
3
approaches zero at these points. These models possess a local segmentation property. They are
sensitive to the position of the initial contour as they are prone to the local minima and can
only segment the desired object with a proper initial contour. As a result, these models fail to
detect the boundaries when the initial contour is far from the boundary of the desired object.
They also cannot detect the interior boundary without setting a proper initial contour inside the
desired object.
Region-based models represent another category of ACMs [11-16]. These models deploy
statistical information inside and outside the contour in order to control its evolution. Region-
based models are less sensitive to the position of the initial contour. They perform well in
the presence of noise and on images with weak edges or without edges. These models have a
global segmentation property and can detect the interior and exterior boundaries at the same
time, regardless of the position of the initial contour in the image. Chan and Vese [11]
proposed a widely used region-based model, namely the CV model. Zhang et al. [12]
proposed a ZAC model which uses statistical information inside and outside the contour to
formulate the signed pressure force when evolving the contour. This paper proposes an improved
ZAC model which can perform well when the edge is weak or blurred.
This paper is organized as follows: Section 2 reviews the CV model [11]. Section 3 reviews
the ZAC model [12]. Section 4 describes our methodology. Section 5 shows some experimental
results and finally the conclusion is made in Section 6.
2. THE CV MODEL
The CV model is based on the Mumford–Shah segmentation technique [13]. It has been
successfully implemented in binary phase segmentation. The CV model uses the statistical
information inside and outside the contour with the aim of controlling the evolution.
The CV model is formulated by minimizing the equation:
( ) ( ) ( )
2 2
1 2 1 0 1 2 0 2
, , ( ) ( , ) ( , )( ) ( )F c c C Length C Area inside C u x y c dxdy u x y c dxdyinside C outside Cµ ν λ λ= + + − + −∫ ∫
(5)
where 0
u is a given image in Ω , µ , v , 21,λ λ are positive parameters and 1 2,c c are the
average intensities inside and outside the curve C , respectively. With the level set method,
one can assume:
( ){ }
( ){ }
( ){ }
1
2
, : ( , ) 0
, : ( , ) 0
, : ( , ) 0
C x y x y
c x y x y
c x y x y
φ
φ
φ
= ∈ Ω =
= ∈ Ω >
= ∈ Ω <
0
1
0
2
( , ) ( ( , ))
( )
( ( , ))
( , )(1 ( ( , )))
( ) (6)
(1 ( ( , )))
u x y H x y dxdy
c
H x y dxdy
u x y H x y dxdy
c
H x y dxdy
φ
φ
φ
φ
φ
φ
Ω
Ω
Ω
Ω
=
−
=
−
∫
∫
∫
∫
4. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
4
where ( )H φ refers to the Heaviside function and ( )δ φ is the Dirac function. The regularization
version of H and δ that were implemented in the C-V model are:
The corresponding variation level set formulation is then:
where µ controls the curve smoothness during the deformation, v is a constant to increase the
propagation speed, and 1λ and 2λ control the image forces inside and outside the contour C ,
respectively. The values of ( )zεδ tend to be near zero, if ε is too small. In this case,
extraction of the desired object may fail if the initial contour starts far from the desired
object. The final contour location may not be accurate if ε is large [12].
3. THE ZAC MODEL
Zhang et al. [12] proposed a novel level set method termed as selective binary and Gaussian
filtering regularized level set (SBGFRLS). This approach selectively penalizes the level set
function to be a binary function. This is followed by using a Gaussian function to regularize it.
The Gaussian filters smooth the level set function and afford the evolution more stability.
SBGFRLS model reduces the computational cost of the re-initialization step which in turn
makes it more efficient than the traditional level set methods [17].
It is worthwhile mentioning that the SBGFRLS method has the advantage of being a general and
robust technique. It can be applied to the classical ACMs, such as the GAC model [ 4] as
well as the CV model [11].
A novel signed pressure force (SPF) [18] is proposed to control the direction of the evolution
and to stop the evolving contour at weak or blurred edges. Zhang et al.’s model is referred as
Zhang et al. active contour (ZAC). The ZAC model uses statistical information inside and
outside the contour to formulate the SPF. The proposed SPF function is assigned with values in
the range [-1, 1]. It modulates the signs of the pressure forces inside and outside the region of
interest as:
1 2
0
0
1 2
0
( )
2( ( )) , (9)
max(| ( ) |)
2
c c
u x
spf u x x
c c
u x
+
−
= ∈Ω
+
−
where 1c and 2c are defined in Eq. (6). The SPF assumes that if the intensities inside and outside
the object are homogenous, it is instinctive that ( )( ) 1Min ou x c<= and ( )( ) 2Max ou x c<= , therefore
( )( ) ( )( )
1 2+
Min Max
2
o o
c c
u x u x< < . The SPF function has opposite signs around the object boundary in
order to force the contour to shrink when it is outside the object and to expand when it is inside
the object.
2 2
1 0 1 2 0 2( ) ( ) ( ) ( ) (8)div u c u c
t
φ φ
δ φ µ φ ν λ λ
φ
∂ ∇
= ∇ − − − + −
∂ ∇
1 2
( ) (1 arctan( ))
2
1
( ) . , (7)
z
H z
z z R
z
ε
ε
π ε
ε
δ
π ε
= +
= ∈
+
5. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
5
The formulation of the level set function in the ZAC model is given as:
0( ( )). | |, (10)spf u x x
t
φ
α φ
∂
= ∇ ∈Ω
∂
The ZAC model utilizes a binary function for the initialization of the level set function φ
instead of using the signed distance function as in the traditional level set method. The ZAC
model deploys the image statistical information to stop the curve evolution on the desired
object boundaries. This makes the ZAC model insensitive to noise and can perform well in the
case of an object with weak edges or without edges. The ZAC model is capable of
performing both local and global segmentation, in contrast to the CV model which can only
handle global segmentation and extracts all the objects. The ZAC model has less
computational complexity than the GAC and CV models.
4. THE PROPOSED MODEL
In this paper, we propose a new edge stopping function that controls the direction of the
evolution and stops the evolving contour at weak or blurred edges. Our model is implemented
using the SBGFRLS method, which grants it a selective local or global segmentation property.
Our model mainly adapts the methodology of the ZAC model [12] yet with improvement. Our
novel modification stems from utilizing a new function termed the global threshold function
(GTF) instead of using the SPF as in the original ZAC model. The GTF operates similarly to
the SPF. Generally, both functions produce similar results. It controls the direction of the
evolution and stops the evolving contour at weak or blurred edges.
Our proposed model performs well when the intensities inside and outside the object are
homogenous and in the binary segmentation phase, in an analogy to the ZAC model. The
GTF has opposite signs around the object boundary in order to force the contour to shrink
when it is outside the object and to expand when it is inside the object. The proposed GTF is
assigned with values in the range [-1, 1] as:
where t is a threshold value computed automatically by using the global thresholding method
[19]. For choosing t automatically, the following algorithm is applied:
1. Select an initial estimate for t. (A suggested initial value is the midpoint between the
minimum and maximum intensity values in the image.)
2. Segment the image using t. This will produce two groups of pixels, G1 consisting of all
pixels with intensity values > t, and G2, consisting of pixels with values <= t.
3. Compute the average intensity values x1 and x2 for the pixels in regions G1 and G2.
4. Compute a new threshold value: t =1/2(x1+x2)
5. Repeat steps 2 through 4 until the difference in t in successive iterations is smaller than a
predefined parameter t0.
The procedure of the proposed algorithm consists of consecutive steps. Firstly, it requires
initialising the level set function into a binary function and computing the value of t and the value
of stopping function according to Eq. (11). In the next step, Eq. (10) is deployed to evolve the
level set function. In this procedure, if the local segmentation property is desired, let φ =1 if φ
0
0
0
( )
( ( )) , (11)
max(| ( ) |)
u x t
gtf u x x
u x t
−
= ∈Ω
−
6. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
6
>0; otherwise φ = -1. A Gaussian filter is to be used to smooth and regularize the level set
function. Finally, the procedure stops upon the convergence of the evolution of the level set
function. The contour could be initialized anywhere inside the image to extract all exterior and
interior boundaries, even if the initial contour does not surround all the objects in the image.
Our model entails all the advantages pertinent to the ZAC model. Our model gives a similar
result to the ZAC model in less computational time because the values of t and 0( ( ))gtf u x
are computed only once. The ZAC model can extract objects with distinctive boundaries while
interior intensities are not homogeneous. By contrast, our model extracts both the interior and
exterior boundaries as shown in Figure 6.
5. EXPERIMENTAL RESULTS
In each experiment, we selected values of ρ , ε , σ , k , and s to be 1, 1.5, 1, 5 and 1,
respectively. The values of α and t were set according to the images. Figure 1 exhibits the
global segmentation property of the proposed model. The initial contour is initialized far from
the objects, as shown in the first row of Figure 1. The second row shows the segmentation
results of our model. Clearly, our model extracts accurately all the objects in the image regardless
of the position of the initial contour.
Figure 1. The first row shows the initial contour; the second row shows
the segmentation results of the proposed method with t corresponding
to 104, 150, 132 and 138 for the first, second, third and fourth column,
respectively and α =20.
Figure 2 exhibits the global segmentation property of the CV model and our proposed model.
The initial contour is initialized far from the objects, as shown in the first image of Figure 2.
The middle image shows the segmentation results of the CV model. As is displayed, the CV
model fails to extract all the objects in the image. The third image shows the segmentation
result of our model. Clearly, our model extracts accurately all the objects in the image regardless
of the position of the initial contour, while the CV model may be trapped into the local minima
resulting in unsatisfactory segmentation.
7. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
7
Figure 2. Comparisons of the global property between the CV model
and the proposed method. The first image shows the initial contour; the
middle image shows the segmentation results of the CV method; and
the third image shows the result of the proposed method with t = 172
and α =20.
Figure 3 presents segmentation results of the CV model and the proposed model in a magnetic
resonance image of the left ventricle of a human heart. In an analogy to the ZAC model, our
model also can selectively extract the desired object by setting the initial contour inside or
surrounding the desired boundaries, while the CV model will extract all the objects. Furthermore,
the evolution direction in our model can be controlled to obtain satisfactory segmentation results,
while the CV model may obtain disordered results.
Figure 3. Segmentation results for a magnetic resonance image of the
left ventricle of a human heart. The first image shows the initial
contour; the middle image shows the segmentation results of the CV
model; and the third image shows the result of the proposed model with
t=111 and α =5.
Figure 4 shows the local segmentation property of the proposed model. The
initial contour resides near or surrounding the desired objects, as shown in the
first row of Figure 4. The second row shows the segmentation results of our
proposed model.
8. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
8
Figure 4. Segmentation results of the proposed model. The first row
shows the initial contours; the second row shows the segmentation
results of the proposed method. t equals to 157, 155,138 for the first,
second and third column, respectively and α =20.
Figure 5 shows the global segmentation results by the proposed model for noisy images. As it can
be seen, despite of the presence of significant noise inherit in the image, our model performs well in
detecting the desired object boundary.
Figure 5. Global segmentation results for a noisy image. The left
image shows the initial contour; the right image shows the
segmentation result of the proposed method with t =125 and α =10.
Figure 6 shows the local segmentation property of the ZAC model and the proposed model. As
shown in Figure 6, the ZAC model extracts objects with distinct boundaries whereas the interior
intensities are not homogeneous. On the contrary, our model extracts the interior and the exterior
boundaries. This represents the main shortcoming of our propose model.
9. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
9
Figure 6. Local segmentation results for a real microscope cell image.
The first image shows the initial contour; the middle image shows the
segmentation results of the ZAC method; and the third image shows the
result of the proposed method with t=94. The original image is sourced
from Zhang et al. [12].
Figure 7 exhibits the performance of our proposed method in the case of Arabic-characters
segmentation. As shown in this figure, our proposed model attains satisfactory segmentation
results.
Figure 7. The left image shows the initial contour; the right image
shows the segmentation results of the proposed method with t = 120
and α =20.
6. CONCLUSIONS
A novel global threshold-based active contour model with a new edge-stopping function has
been presented. The main merits of this approach consist of its ability to control the direction of
the evolving contour and to stop it on the weak or blurred edges. Our model is implemented
using the SBGFRLS method. We tested this method on several categories of images including
synthetic, medical and Arabic-characters where a satisfactory performance was attained.
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AUTHORS
Nuseiba Altarawneh is a PhD student at the University of Newcastle, Australia. Her
research interests include computer vision, image analysis, and pattern recognition. She
obtained M.E. degrees in Computer science from the University of Jordan in 2009.
Dr. Suhuai Luo received PhD degree in Electrical Engineering from the University of
Sydney Australia in 1995. From 1995 to 2004, he worked as a senior research scientist
with the Commonwealth Scientific and Industrial Research Organization Australia and the
Bioinformatics Institute Singapore. He is currently a senior lecturer with the University of
Newcastle Australia. His research interest is in information technology and multimedia,
including health informatics, machine learning, image processing, computer vision, and
Internet-oriented IT applications.
Dr Brian Regan is a senior lecturer in IT at the University of Newcastle. He is part of the
Applied Informatics Research Group (AIR) with interests in health informatics,
visualization and development methodologies.
11. Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.3, June 2014
11
Dr. Changming Sun received the PhD degree in the area of computer vision from
Imperial College London in 1992. Then, he joined CSIRO Computational Informatics,
Australia, where he is currently a principal research scientist carrying out research and
working on applied projects. His research interests include computer vision, image
analysis, and pattern recognition. He has served on the program/organizing committees of
various international conferences. He is an Associate Editor for EURASIP Journal on
Image and Video Processing, a SpringerOne journal.
Dr. Fucang Jia received PhD degreee in computer application technology from Institute of
Computing Technology, Chinese Academy of Sciences in 2004. In 2004-2008, he worked
as a research engineer in Shenzhen Anke High-Tech Co., Ltd. From 2008, he joined
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences as an
associate research fellow. His research interests are in computer assisted surgery and
machine learning.