The document describes an improved SIFT feature extraction and matching algorithm based on the MSER algorithm. It first uses MSER instead of DOG to detect maximally stable elliptical regions, increasing stability and reducing the number of features. It then divides each elliptical region into fan-shaped subregions instead of square subregions, and constructs a new SIFT descriptor using Gaussian-weighted gradient information. Experimental results showed the new algorithm has affine invariance while maintaining other properties of SIFT, making it faster and better suited for real-time image processing.
This project is to retrieve the similar geographic images from the dataset based on the features extracted.
Retrieval is the process of collecting the relevant images from the dataset which contains more number of
images. Initially the preprocessing step is performed in order to remove noise occurred in input image with
the help of Gaussian filter. As the second step, Gray Level Co-occurrence Matrix (GLCM), Scale Invariant
Feature Transform (SIFT), and Moment Invariant Feature algorithms are implemented to extract the
features from the images. After this process, the relevant geographic images are retrieved from the dataset
by using Euclidean distance. In this, the dataset consists of totally 40 images. From that the images which
are all related to the input image are retrieved by using Euclidean distance. The approach of SIFT is to
perform reliable recognition, it is important that the feature extracted from the training image be
detectable even under changes in image scale, noise and illumination. The GLCM calculates how often a
pixel with gray level value occurs. While the focus is on image retrieval, our project is effectively used in
the applications such as detection and classification.
Image segmentation techniques
More information on this research can be found in:
Hussein, Rania, Frederic D. McKenzie. “Identifying Ambiguous Prostate Gland Contours from Histology Using Capsule Shape Information and Least Squares Curve Fitting.” The International Journal of Computer Assisted Radiology and Surgery ( IJCARS), Volume 2 Numbers 3-4, pp. 143-150, December 2007.
Efficient 3D stereo vision stabilization for multi-camera viewpointsjournalBEEI
In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing
the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method.
Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.
This project is to retrieve the similar geographic images from the dataset based on the features extracted.
Retrieval is the process of collecting the relevant images from the dataset which contains more number of
images. Initially the preprocessing step is performed in order to remove noise occurred in input image with
the help of Gaussian filter. As the second step, Gray Level Co-occurrence Matrix (GLCM), Scale Invariant
Feature Transform (SIFT), and Moment Invariant Feature algorithms are implemented to extract the
features from the images. After this process, the relevant geographic images are retrieved from the dataset
by using Euclidean distance. In this, the dataset consists of totally 40 images. From that the images which
are all related to the input image are retrieved by using Euclidean distance. The approach of SIFT is to
perform reliable recognition, it is important that the feature extracted from the training image be
detectable even under changes in image scale, noise and illumination. The GLCM calculates how often a
pixel with gray level value occurs. While the focus is on image retrieval, our project is effectively used in
the applications such as detection and classification.
Image segmentation techniques
More information on this research can be found in:
Hussein, Rania, Frederic D. McKenzie. “Identifying Ambiguous Prostate Gland Contours from Histology Using Capsule Shape Information and Least Squares Curve Fitting.” The International Journal of Computer Assisted Radiology and Surgery ( IJCARS), Volume 2 Numbers 3-4, pp. 143-150, December 2007.
Efficient 3D stereo vision stabilization for multi-camera viewpointsjournalBEEI
In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing
the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method.
Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.
PERFORMANCE EVALUATION OF SPATIAL AND FRACTAL WATERMARKING ALGORITHMAM Publications
Recent days watermarking plays a vital role in most of the industries for security purpose. In this paper, we
compare both spatial and fractal Watermarking algorithms. We have been improving the resistance in data compression.
The composition of all these transformations has the image as its fixed point. Starting with any image hence to apply the
composition of the transformations repeatedly and get an approximation of the original image
APPLYING R-SPATIOGRAM IN OBJECT TRACKING FOR OCCLUSION HANDLINGsipij
Object tracking is one of the most important problems in computer vision. The aim of video tracking is to extract the trajectories of a target or object of interest, i.e. accurately locate a moving target in a video sequence and discriminate target from non-targets in the feature space of the sequence. So, feature descriptors can have significant effects on such discrimination. In this paper, we use the basic idea of many trackers which consists of three main components of the reference model, i.e., object modeling, object detection and localization, and model updating. However, there are major improvements in our system. Our forth component, occlusion handling, utilizes the r-spatiogram to detect the best target candidate. While spatiogram contains some moments upon the coordinates of the pixels, r-spatiogram computes region-based compactness on the distribution of the given feature in the image that captures richer features to represent the objects. The proposed research develops an efficient and robust way to keep tracking the object throughout video sequences in the presence of significant appearance variations and severe occlusions. The proposed method is evaluated on the Princeton RGBD tracking dataset considering sequences with different challenges and the obtained results demonstrate the effectiveness of the proposed method.
Radial Fourier Analysis (RFA) Descriptor with Fourier-based Keypoint OrientationCSCJournals
Local keypoint detection and description have been widely employed in a large number of computer vision applications, such as image registration, object recognition and robot localisation. Since currently available local keypoint descriptors are based on the uses of statistical analysis in spatial domain, a local keypoint descriptor, namely Radial Fourier Analysis (RFA) keypoint descriptor, is developed with the use of spectral analysis in frequency domain. This descriptor converts image gradients around SIFT keypoints to frequency domain in order to extract the principle components of the gradients and derive distinctive descriptions for representing the keypoints. Additionally, a keypoint orientation estimate is also introduced to improve the rotational invariance of the descriptor rather than simply adopting SIFT keypoint orientations. The introduced orientation estimate employs the starting point normalisation of Fourier coefficients, which are frequency responses, to deduce rotating angles that ensure keypoint correspondences are aligned at the same orientation. Through experiments and comparisons, RFA descriptor demonstrates its outstanding and robust performances against various image distortions. Particularly, the descriptor has extremely reliable performances in dealing with the images, which are degraded by blurring, JPG compression and illumination changes. All these indicate that spectral analysis has strong potential for local keypoint description.
Noise Removal with Morphological Operations Opening and Closing Using Erosio...IJMER
The mathematical operations are proposed in this paper. By using two mathematical
operations erosion and dilation we can add and remove pixels. We can remove the noise or interference in
power system. Opening and closing operations also discussed with erosion and dilation. These four
morphological operations are also helpful in developing a morphological filter.
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.
Data-Driven Motion Estimation With Spatial AdaptationCSCJournals
The pel-recursive computation of 2-D optical flow raises a wealth of issues, such as the treatment of outliers, motion discontinuities and occlusion. Our proposed approach deals with these issues within a common framework. It relies on the use of a data-driven technique called Generalised Cross Validation to estimate the best regularisation scheme for a given pixel. In our model, the regularisation parameter is a general matrix whose entries can account for different sources of error. The motion vector estimation takes into consideration local image properties following a spatially adaptive approach where each moving pixel is supposed to have its own regularisation matrix. Preliminary experiments indicate that this approach provides robust estimates of the optical flow.
At the end of this lesson, you should be able to;
define segmentation.
Describe edge based in segmentation.
describe thresholding and its properties.
apply edge detection and thresholding as segmentation techniques.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
Denoising Process Based on Arbitrarily Shaped WindowsCSCJournals
Many factors, such as moving objects, introduce noise in digital images. The presence of noise affects image quality. The image denoising process works on reconstructing a noiseless image and improving its quality. When an image has an additive white Gaussian noise (AWGN) then denoising becomes a challenging process. In our research, we present an improved algorithm for image denoising in the wavelet domain. Homogenous regions for an input image are estimated using a region merging algorithm. The local variance and wavelet shrinkage algorithm are applied to denoise each image patch. Experimental results based on peak signal to noise ratio (PSNR) measurements showed that our algorithm provided better results compared with a denoising algorithm based on a minimum mean square error (MMSE) estimator.
Design and optimization of compact freeform lens array for laser beam splitti...Milan Maksimovic
"Design and optimization of compact freeform lens array for laser beam splitting: a case study in optimal surface representation", in Optical Modelling and Design III, Frank Wyrowski; John T. Sheridan; Jani Tervo; Youri Meuret, Editors, Proceedings of SPIE Vol. 9131 (SPIE, Bellingham, WA 2014), 913107.
At the end of this lesson, you should be able to;
describe Connected Components and Contours in image segmentation.
discuss region based segmentation method.
discuss Region Growing segmentation technique.
discuss Morphological Watersheds segmentation.
discuss Model Based Segmentation.
discuss Motion Segmentation.
implement connected components, flood fill, watershed, template matching and frame difference techniques.
formulate possible mechanisms to propose segmentation methods to solve problems.
PERFORMANCE EVALUATION OF SPATIAL AND FRACTAL WATERMARKING ALGORITHMAM Publications
Recent days watermarking plays a vital role in most of the industries for security purpose. In this paper, we
compare both spatial and fractal Watermarking algorithms. We have been improving the resistance in data compression.
The composition of all these transformations has the image as its fixed point. Starting with any image hence to apply the
composition of the transformations repeatedly and get an approximation of the original image
APPLYING R-SPATIOGRAM IN OBJECT TRACKING FOR OCCLUSION HANDLINGsipij
Object tracking is one of the most important problems in computer vision. The aim of video tracking is to extract the trajectories of a target or object of interest, i.e. accurately locate a moving target in a video sequence and discriminate target from non-targets in the feature space of the sequence. So, feature descriptors can have significant effects on such discrimination. In this paper, we use the basic idea of many trackers which consists of three main components of the reference model, i.e., object modeling, object detection and localization, and model updating. However, there are major improvements in our system. Our forth component, occlusion handling, utilizes the r-spatiogram to detect the best target candidate. While spatiogram contains some moments upon the coordinates of the pixels, r-spatiogram computes region-based compactness on the distribution of the given feature in the image that captures richer features to represent the objects. The proposed research develops an efficient and robust way to keep tracking the object throughout video sequences in the presence of significant appearance variations and severe occlusions. The proposed method is evaluated on the Princeton RGBD tracking dataset considering sequences with different challenges and the obtained results demonstrate the effectiveness of the proposed method.
Radial Fourier Analysis (RFA) Descriptor with Fourier-based Keypoint OrientationCSCJournals
Local keypoint detection and description have been widely employed in a large number of computer vision applications, such as image registration, object recognition and robot localisation. Since currently available local keypoint descriptors are based on the uses of statistical analysis in spatial domain, a local keypoint descriptor, namely Radial Fourier Analysis (RFA) keypoint descriptor, is developed with the use of spectral analysis in frequency domain. This descriptor converts image gradients around SIFT keypoints to frequency domain in order to extract the principle components of the gradients and derive distinctive descriptions for representing the keypoints. Additionally, a keypoint orientation estimate is also introduced to improve the rotational invariance of the descriptor rather than simply adopting SIFT keypoint orientations. The introduced orientation estimate employs the starting point normalisation of Fourier coefficients, which are frequency responses, to deduce rotating angles that ensure keypoint correspondences are aligned at the same orientation. Through experiments and comparisons, RFA descriptor demonstrates its outstanding and robust performances against various image distortions. Particularly, the descriptor has extremely reliable performances in dealing with the images, which are degraded by blurring, JPG compression and illumination changes. All these indicate that spectral analysis has strong potential for local keypoint description.
Noise Removal with Morphological Operations Opening and Closing Using Erosio...IJMER
The mathematical operations are proposed in this paper. By using two mathematical
operations erosion and dilation we can add and remove pixels. We can remove the noise or interference in
power system. Opening and closing operations also discussed with erosion and dilation. These four
morphological operations are also helpful in developing a morphological filter.
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.
Data-Driven Motion Estimation With Spatial AdaptationCSCJournals
The pel-recursive computation of 2-D optical flow raises a wealth of issues, such as the treatment of outliers, motion discontinuities and occlusion. Our proposed approach deals with these issues within a common framework. It relies on the use of a data-driven technique called Generalised Cross Validation to estimate the best regularisation scheme for a given pixel. In our model, the regularisation parameter is a general matrix whose entries can account for different sources of error. The motion vector estimation takes into consideration local image properties following a spatially adaptive approach where each moving pixel is supposed to have its own regularisation matrix. Preliminary experiments indicate that this approach provides robust estimates of the optical flow.
At the end of this lesson, you should be able to;
define segmentation.
Describe edge based in segmentation.
describe thresholding and its properties.
apply edge detection and thresholding as segmentation techniques.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
Denoising Process Based on Arbitrarily Shaped WindowsCSCJournals
Many factors, such as moving objects, introduce noise in digital images. The presence of noise affects image quality. The image denoising process works on reconstructing a noiseless image and improving its quality. When an image has an additive white Gaussian noise (AWGN) then denoising becomes a challenging process. In our research, we present an improved algorithm for image denoising in the wavelet domain. Homogenous regions for an input image are estimated using a region merging algorithm. The local variance and wavelet shrinkage algorithm are applied to denoise each image patch. Experimental results based on peak signal to noise ratio (PSNR) measurements showed that our algorithm provided better results compared with a denoising algorithm based on a minimum mean square error (MMSE) estimator.
Design and optimization of compact freeform lens array for laser beam splitti...Milan Maksimovic
"Design and optimization of compact freeform lens array for laser beam splitting: a case study in optimal surface representation", in Optical Modelling and Design III, Frank Wyrowski; John T. Sheridan; Jani Tervo; Youri Meuret, Editors, Proceedings of SPIE Vol. 9131 (SPIE, Bellingham, WA 2014), 913107.
At the end of this lesson, you should be able to;
describe Connected Components and Contours in image segmentation.
discuss region based segmentation method.
discuss Region Growing segmentation technique.
discuss Morphological Watersheds segmentation.
discuss Model Based Segmentation.
discuss Motion Segmentation.
implement connected components, flood fill, watershed, template matching and frame difference techniques.
formulate possible mechanisms to propose segmentation methods to solve problems.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
EFFECTIVE INTEREST REGION ESTIMATION MODEL TO REPRESENT CORNERS FOR IMAGE sipij
One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region
around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new local maxima-based
interest region detection method. This region estimation method can be used to build descriptors to represent corners. We have performed a comparative analysis to match the feature points using recent corner detectors and the result shows that our method achieves better precision and recall results than
existing methods.
Object tracking with SURF: ARM-Based platform ImplementationEditor IJCATR
Several algorithms for object tracking, are developed, but our method is slightly different, it’s about how to adapt and implement such algorithms on mobile platform.
We started our work by studying and analyzing feature matching algorithms, to highlight the most appropriate implementation technique for our case.
In this paper, we propose a technique of implementation of the algorithm SURF (Speeded Up Robust Features), for purposes of recognition and object tracking in real time. This is achieved by the realization of an application on a mobile platform such a Raspberry pi, when we can select an image containing the object to be tracked, in the scene captured by the live camera pi. Our algorithm calculates the SURF descriptor for the two images to detect the similarity therebetween, and then matching between similar objects. In the second level, we extend our algorithm to achieve a tracking in real time, all that must respect raspberry pi performances. So, the first thing is setting up all libraries that the raspberry pi need, then adapt the algorithm with card’s performances. This paper presents experimental results on a set of evaluation images as well as images obtained in real time.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
Local Phase Oriented Structure Tensor To Segment Texture Images With Intensit...CSCJournals
This paper proposed the active contour based texture image segmentation scheme using the linear structure tensor and tensor oriented steerable Quadrature filter. Linear Structure tensor (LST) is a popular method for the unsupervised texture image segmentation where LST contains only horizontal and vertical orientation information but lake in other orientation information and also in the image intensity information on which active contour is dependent. Therefore in this paper, LST is modified by adding intensity information from tensor oriented structure tensor to enhance the orientation information. In the proposed model, these phases oriented features are utilized as an external force in the region based active contour model (ACM) to segment the texture images having intensity inhomogeneity and noisy images. To validate the results of the proposed model, quantitative analysis is also shown in terms of accuracy using a Berkeley image database.
SHORT LISTING LIKELY IMAGES USING PROPOSED MODIFIED-SIFT TOGETHER WITH CONVEN...ijfcstjournal
The paper proposes the modified-SIFT algorithm which will be a modified form of the scale invariant feature transform. The modification consists of considering successive groups of 8 rows of pixel, along the height of the image. These are used to construct 8 bin histograms for magnitude as well as orientation individually. As a result the number of feature descriptors is significantly less (95%) than the standard SIFT approach. Fewer feature descriptor leads to reduced accuracy. This reduction in accuracy is quite drastic when searching for a single (RANK1) image match; however accuracy improves if a band of likely (say tolerance of 10%) images is to be returned. The paper therefore proposes a two-stage-approach where
First Modified-SIFT is used to obtain a shortlisted band of likely images subsequently SIFT is applied within this band to find a perfect match. It may appear that this process is tedious however it provides a significant reduction in search time as compared to applying SIFT on the entire database. The minor reduction in accuracy can be offset by the considerable time gained while searching a large database. The
modified-SIFT algorithm when used in conjunction with a face cropping algorithm can also be used to find a match against disguised images.
Research on Image Classification Model of Probability Fusion Spectrum-Spatial...CSCJournals
For insufficient information of imaging spectrum with high spatial resolution, detailed imaging information, reduction of mixed pixels, increase of pure pixels and problems of image characteristic extraction and model classification produced from this, we provide a classifier model of a united spectrum-spatial multi-characteristic based on SVM, and use this model to finish the image classification. The model completely uses the multi-characteristic information, and overcomes the over-fitting problems produced by accumulating high-dimensional characteristics. The model includes three classifications of spectrum-spatial characteristics, namely spectral characteristics-spectral characteristic of multi-scale morphology, spectral characteristics-physical characteristics of underlaying surfaces of multi-scale morphology and spectral characteristics-features spatial extension characteristics of multi-scale morphology. Firstly the three classifications of spectrum-spatial characteristics are classified through SVM, then carries out the probability fusion for the classification results based on the pixels to obtain the final image classification results. This article respectively uses WorldView-2 image and ROSIS image to experiment, and the results show that the model has better classification effect compared with VS-SVM algorithm.
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.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Similar to Improved Characters Feature Extraction and Matching Algorithm Based on SIFT (20)
Technology Content Analysis with Technometric Theory Approach to Improve Perf...Nooria Sukmaningtyas
Radiologic installation be facilitated with medical equipment for supporting of health services in
investigation of disease. There are 3 (three) criteria technology of equipment: investigation with
sophisticated equipment (CT scans single slice), investigation with a medium-sized enterprises equipment
(general x-ray 300 mA / 125 KV) and simple equipment (Portable Dental x-ray 8mA /70 KV). In view of
contribution to the Hospital, Radiologic installation from 2008 until 2012 has decreased, the data as
follows: The year 2008 was 6.8 percent; in 2009 was 4.3 percent; in 2010 was 2.5 percent; in 2011 was
2.3 percent; and in 2012 was 2.6 percent.By using approach of technometric theory, the study measures
the significant contribution of each component of technology that consists of aspects: Technoware,
Humanware, Inforware, Orgaware in Radiologic Installation, and also want to know about the
sophistication of the technology which is used in indicators Technology contribution coefficien (TCC), so
factors that affect experienced performance result can be known, where TCC are: TCC High Technology
TCC_tt =0,490 if T_tt= 0,387 H= 0,519 I= 0,538 O=0,534 TCC Middle technology TCC_tm=0,443 if
T_tm=0,258 H=0,519 I=0,538 O=0,534TCC Simple technology TCC_ts =0,398 if T_ts=0,168 H=0,519
I=0,538 O=0,534If the value of component technology (T,H,I,O) is less than TCC, its means that
Radiologic Installation Unit is in decreasing phase, a condition that cannot be left, need the directors’s
action immediately to formulate the right and fast policies to protect it from lost. The final result of study is a
gap almost everywhere from the three technology component Humanware = 0,519, Inforware = 0,538,
Orgaware = 0,534, but the gap between most components in technology aspects Technoware (0,387,
0,258, 0,168), that means that development strategy of Radiologic Installation unit be prioritized on
increasing aspects Technoware (rejuvenation medical equipment).
Data Exchange Design with SDMX Format for Interoperability Statistical DataNooria Sukmaningtyas
Today’s concept of Open Government Data (OGD) for openness, transparency and ease of
access of data owned by government agencies becomes increasingly important. This initiative emerges
from the demand of data usersforthe data belongs to the government agencies. The data services
providing an easy access, cheap, fast, and interoperability are needed by the users and becomes
important indicator performance for respective government agencies. Statistical Data and Metadata
Exchange (SDMX) is a new standard format in the data dissemination activities particularly in the
exchange of statistical data and metadata via Internet. In this respect SDMX support the implementation of
OGD project. This paper is on the technical design, development and implementation of data and
metadata exchange service of statistical data using SDMX format to support interoperability data through
web services. Three results are proposed: (i) framework for standardization of structure of statistical
publications data model with SDMX; (ii) design architecture of data sharing model; and (iii) web service
implementation of data and metadata exchange service using Service Oriented Analysis and Design
(SOAD) method. Implementation at Statistics Indonesia (BPS) is chosen as a case study to prove the
design concept. It is shown through quantitative assessment and black box testing that the design
achieves its objective.
The knowledge management is a model involving the information system in the knowledge
processing. “Tim Penyelesaian Kerugian Negara” (TPKN) is one of sources of information related to the
state loss settlement, so it needs the development of knowledge management system on the state loss
settlement to ease the users when looking for the references of knowledge as completely as possible,
accurately, and quickly. This research aims to develop the system of knowledge management on the state
loss in LAPAN (SIMAPKLA). The used research methodology is Knowledge Management System Life
Cycle (KMSLC). The tacit, explicit knowledge is taken from the experts and it is stored in the Knowledge
Base (KB). The design model uses the approach with the orientation of object and implementation with Yii
Framework and blackbox testing. The menu on this system includes home, about us, dictionary, news,
meeting schedulles, knowledge about state loss, e-document, progress, forum, and contact us. Based on a
series of tests, in the aspect of functionality, this system is suitable and useful to share knowledge and
know the development of state loss settlement.
Automatic Extraction of Diaphragm Motion and Respiratory Pattern from Time-se...Nooria Sukmaningtyas
Thoracic time-sequential MRI can be used to assess diaphragm motion pattern without exposing
radiation to subject. Clinicians may employ the motion to evaluate the severeness of chronic obstructive
pulmonary disease (COPD). This study proposed a novel method of diaphragm motion extraction method
on time-sequential thoracic MRI in sagittal plane. Otsu’s threshold and active contour algorithm are used to
obtain diaphragm boundary. An automatic diaphragm motion tracking and extraction of respiratory pattern
are also performed based on the diaphragm boundary. A total of 1200 frames time-sequential MRI in
sagittal plane was obtained for total of 15 subjects (8 healthy volunteers and 7 COPD patients). The
proposed method successfully extracts diaphragm motion and respiratory patterns for both healthy
volunteers and COPD patients.
A dual-frequency microstrip patch antennas has been presented and used for 802.11WLAN
applications. The antennas had been designed, simulated and parametrically studied in CST Microwave
studio. By introducing u-slot, dual-band operation with its operating mode centered at frequency 2.4GHz,
3.65GHz and 5.2GHz had been obtained. The gain and directivity had been improved by adjusting the
parameters of the antennas. The gain of the proposed designs was 6.019dBi, 4.04dBi and 6.22dBi and
directivity was 6.02dBi, 4.05dBi and 6.22dBi at resonant frequencies 2.4GHz, 3.6GHz and 5.2GHz
respectively. The patch antennas had been proposed to be used in portable devices that require
miniaturized constituent parts.
The Detection of Straight and Slant Wood Fiber through Slop Angle Fiber FeatureNooria Sukmaningtyas
Quality control is one of important process that can not be avoided in industry. Image processing
technique is required to distinguish the quality of wood. If it can be done automatically by the computer, it
will be very helpful. This paper discusses the detection of straight and slant wood fiber to distinguish its
quality. This paper proposes an algorithm by using only two features i.e. mean (average value of slop
angle fiber) and maximumangle (the maximum value of slop angle fiber). Then the classification method is
used by tresholding. The result shows the performance is achieved on accuracy 79.2%
Active Infrared Night Vision System of Agricultural VehiclesNooria Sukmaningtyas
Active infrared night vision system was significant for night driving and it has been greatly used on
limousine car. Design active infrared night vision system for agricultural vehicles greatly improved the night
vision of them and it was an inevitable trend. Comparing parameters of various night vision systems and
designing active infrared night vision system of agricultural vehicles was significant for improving active
security of agricultural vehicles working at nighttime. By analyzing the infrared night vision system basic
parameters determined the structure form and basic parameters, calculated the infrared light wave width
and emission power to choose each components, designed active infrared night vision system’s structure
and determined parameters of agricultural vehicles.
Robot Three Dimensional Space Path-planning Applying the Improved Ant Colony ...Nooria Sukmaningtyas
To make robot avoid obstacles in 3D space, the Pheromone of Ant Colony Optimization (ACO) in
Fuzzy Control Updating is put forward, the Pheromone Updating value varies with The number of iterations
and the path-planning length by each ant . the improved Transition Probability Function is also proposed,
which makes more sense for each ant choosing next feasible point .This paper firstly, describes the Robot
Workspace Modeling and its path-planning basic method, which is followed by introducing the improved
designing of the Transition Probability Function and the method of Pheromone Fuzzy Control Updating of
ACO in detail. At the same time, the comparison of optimization between the pre-improved ACO and the
improved ACO is made. The simulation result verifies that the improved ACO is feasible and available.
Research on a Kind of PLC Based Fuzzy-PID Controller with Adjustable FactorNooria Sukmaningtyas
A kind of fuzzy-PID controller with adjustable factor is designed in this paper. Scale factor’s selfadjust
will come true. Fuzzy control algorithm is finished in STEP7 software, and then downloaded in S7-
300 PLC. WinCC software will be used to control the change-trend in real time. Data communication
between S7-300 PLC and WinCC is achieved by MPI. The research shows that this fuzzy-PID controller
has better robust capability and stability. It’s an effective method in controlling complex long time-varying
delay systems.
This paper proposed a nonlinear robust control for spacecraft attitude based on passivity and
disturbance suppression vector. The spacecraft model was described using quaternion. The control law
introduced the suppression vector of external disturbances and had no information related to the system
parameters. The desired performance of spacecraft attitude control could be achieved using the designed
control law. And stability conditions of the nonlinear robust control for spacecraft attitude were given. The
stability could be proved by applying Lyapunov approach. The verification of the proposed attitude control
method was performed through a series of simulations. The numerical results showed the effectiveness of
the proposed control method in controlling the spacecraft attitude in the presence of external disturbances.
The main benefit of the proposed attitude control method does not need angular velocity measurement
and has its robustness against model uncertainties and external disturbances.
Remote Monitoring System for Communication Base Based on Short MessageNooria Sukmaningtyas
The automatic monitoring system of communication base which is an important means to realize
modernization of mobile communication base station management. In this paper, we implement a
monitoring system for communication base with three essential functions which are telemetry, remote
control and communication. In this system, data acquisition unit, data transmit unit and monitoring centre
unit are combined to form this monitoring system. The system can check the communication base status
anytime through GSM SMS (short message service), and can send predefined command to perform
remote data collection and monitoring in the special conditions. It is suitable especially for the alarm of
unusual situation, the monitoring of environmental information and entrance guard information. The paper,
firstly, proposes the architecture of the monitoring system; secondly, proposes the terminal of monitoring
system. The data collection terminal is studied and designed, including hardware design based on
embedded system and software design. Finally, presents implmentation and results. The monitoring
system can improve the integrity, reliability, flexibility and intellectuality of monitoring system. The system
with modular structure, which is low-cost, fitter and easier to move and operate, can be expanded
according to practical need and is reliable and effective through field test.
Tele-Robotic Assisted Dental Implant Surgery with Virtual Force FeedbackNooria Sukmaningtyas
The dental implant surgical applications full of risk because of the complex anatomical
architecture of craio-maxillofacial area. Therefore, the surgeons move towards computer-aided planning
for surgeries and then implementation using robotic assisted tele-operated techniques. This study divided
into four main parts. The first part is developed by computer-aided surgical planning by image modalities.
The second part is based on Virtual Surgical Environment through virtual force feedback haptic device.
The third part is implemented the experimental surgery by integrating the prototype surgical manipulator
with the haptic device poses using inverse kinematics method. The fourth part based on monitoring the
robotic manipulator pose by using image guided navigation system to calculate the position error of the
surgical manipulator. Thus, this tele-robotic system is able to comprehend the sense of complete practice,
improve skills and gain experience of the surgeon during the surgery. Finally, the experimental outcomes
show in satisfactory boundaries.
This paper proposes an adaptation mechanism based on adaptation planning graph for servicebased
business processes. First, a three-layer representation model of service-based business process is
introduced. Second, control-flow patterns of tasks, goal, logic model of service-based business process
and adaptation planning graph are introduced to enforce reliability of composite web services at run-time.
Finally, a simulation example of adaptation in service-based business processes is given. Simulations
prove that this approach can efficiently guarantee the reliability of composite services at run-time.
Review on Islanding Detection Methods for Photovoltaic InverterNooria Sukmaningtyas
Solar power generation, which is regarded as an ideal environment-friendly manner for power
generation, is getting more and more attention. When photovoltaic inverter is connected to the grid, the
island effect is a special problem to confront. This paper briefly analyzes the island effects and makes a
summary of both domestic and external research progress concerning islanding detection methods; the
islanding detection methods can be divided into two classes: one is grid-side detection; the other is local
detection. The local detection is generally divided into passive methods and active methods. The theory of
advantages and disadvantages of those methods are briefly introduced in this paper. At the end of the
paper, to deal with the disadvantages of those methods that are mentioned, it proposes the research
direction for deeper study of islanding detection methods.
Stabilizing Planar Inverted Pendulum System Based on Fuzzy Nine-point ControllerNooria Sukmaningtyas
In order to stabilize planar inverted pendulum, after analyzing the physical characteristics of the
planar inverted pendulum system, a pendulum nine-point controller and a car nine-point controller for Xaxis
and Y-axis were designed respectively. Then a fuzzy coordinator was designed using the fuzzy
control theory based on the priority of those two controllers, and the priority level of the pendulum is higher
than the car. Thus, the control tasks of each controller in each axis were harmonized successfully. The
designed control strategy did not depend on mathematical model of the system; it depended on the control
experience of people or the control experts. The compared experiments showed that the control strategy
was easy and effective, what was’s more; it had a very good robust feature.
Gross Error Elimination Based on the Polynomial Least Square Method in Integr...Nooria Sukmaningtyas
The measurement data of parameter in the electrical equipment contains many noises in subway
integrated monitoring system. To eliminate the impact of gross error in the measurement data, a
polynomial least square curve fitting algorithm is used in this paper. Based on the Rajda criterion, the
algorithm gives the variance estimation of the noises, and then uses dynamic threshold to detect and
replace the measurement data with gross error by statistical estimation. Finally, a data processing
procedure has been presented to deal with the gross error. The practical application indicates that the
proposed algorithm can effectively eliminate the gross error in many types of measurement signals so as
to ensure the reliability of the monitoring system.
Design on the Time-domain Airborne Electromagnetic Weak Signal Data Acquisiti...Nooria Sukmaningtyas
According to principle of transient electromagnetic method as well as its signal characteristics,
this paper designed and implemented a time-domain airborne electromagnetic weak signal data
acquisition system. With the use of the floating-point amplification technology, the system amplifies the
weak transient electromagnetic signal dynamically. CPLD and DSP were used as the decoding control
circuit and the main controller for processing the sampled data, respectively. The transient electromagnetic
signal acquisition system, which was designed with a dynamic range up to 144dB and a sampling rate up
to 100 kHz, meets the requirements of the high sampling rate with high precision and it has been applied in
the time-domain fixed-wing airborne electromagnetic mineral exploration.
INS/GPS integrated navigation system is studied in this paper for the hypersonic UAV in order to
satisfy the precise guidance requirements of hypersonic UAV and in response to the defects while the
inertial navigation system (INS) and the global positioning system (GPS) are being applied separately. The
information of UAV including position, velocity and attitude can be obtained by using INS and GPS
respectively after generating a reference trajectory. The corresponding errors of two navigation systems
can be obtained through comparing the navigation information of the above two guidance systems.
Kalman filter is designed to estimate the navigation errors and then the navigation information of INS are
corrected. The non-equivalence relationship between the platform misalignment angle and attitude error
angle are considered so that the navigation accuracy is further improved. The Simulink simulation results
show that INS/GPS integrated navigation system can help to achieve higher accuracy and better antiinterference
ability than INS navigation system and this system can also satisfy the navigation accuracy
requirements of hypersonic UAV.
Research on Space Target Recognition Algorithm Based on Empirical Mode Decomp...Nooria Sukmaningtyas
The space target recognition algorithm, which is based on the time series of radar cross section
(RCS), is proposed in this paper to solve the problems of space target recognition in the active radar
system. In the algorithm, EMD method is applied for the first time to extract the eigen of RCS time series.
The normalized instantaneous frequencies of high-frequency intrinsic mode functions obtained by EMD are
used as the eigen values for the recognition, and an effective target recognition criterion is established.
The effectiveness and the stability of the algorithm are verified by both simulation data and real data. In
addition, the algorithm could reduce the estimation bias of RCS caused by inaccurate evaluation, and it is
of great significance in promoting the target recognition ability of narrow-band radar in practice.
With the expanding of database of the watch list of anti-money laundering, improving the speed in
matching between the watch list and the database of account holders and clients’ transaction is especially
important. This paper proposes an improved AC-BM Algorithm, a matching algorithm of subsection, to
improve the speed of matching. Experiment results show the time performance of the improved algorithm
is better than traditional BM algorithm, AC algorithm and the AC-BM algorithm. It can improve the
efficiency of on-line monitoring of anti-money laundering.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
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to calculate the main direction of the region after normalizing the extracted affine invariant
elliptical area into a circular area, use SIFT to produce a 128 element descriptor vector and
reduce the dimension of 128 element feature vector by the use of PCA (Principal Component
Analysis) [13], in order to improve operation efficiency. Numerical experiments verify the
effectiveness of the new method
2. Structure of SIFT Descriptor
The structure of SITF operator mainly includes four stages [10]: DOG scale-space
extreme detection, accurate key point location, Orientation assignment, the establishment of
feature descriptor.
2.1. Extreme Detection of DOG Scale-Space
Gaussian kernel function is used to analyze the image scale transformation, and
adjacent Gaussian images are subtracted to produce the difference-of-Gaussian (DOG) images
that build DOG pyramid. Then the local maxima and minima of the difference-of-Gaussian
images which will be determined as candidate feature points are detected by comparing a pixel
to its 26 neighbors in 3*3 regions at the current and adjacent scales. The cost of this check is
reasonably low due to the fact that most sample points will be eliminated following the first few
checks.
The scale space of an image is defined as a function, ),,( yxL , that is produced from
the convolution of a variable-scale Gaussian, ),,( yxG ,with an input image, ),( yxI :
),(),,(),,( yxIyxGyxL (1)
Where is the scale of an image, is the convolution operation in x and y, and
),,( yxG is a two dimensional Gaussian function, and
222
2/)(
2
2
1
),,(
yx
eyxG
(2)
2.2. Accurate Key Point Localization
Once a keypoint candidate has been found by comparing a pixel to its neighbors, the
next step is to perform a detailed fit to the nearby data for location, scale, and ratio of principal
curvatures.
In the SIFT algorithm, in order to improve the stability of the key points, we need a
curve fitting for DOG function of scale space. Using the Taylor expansion of the scale-space
DOG function:
x
x
xx
x
0x 2
2
2
1
)()(
ff
ff T
T
(3)
Where )(xf and its derivatives are evaluated at the sample point and ),,( yxx is the
offset from this point. The location of the extremum ˆx is determined by taking the derivative of
this function with respect to x and setting it to zero, giving
xx
x
ff 1-2
(4)
This function value at the extremum, ˆ( )f x , is useful for rejecting unstable extrema with
low contrast. This can be obtained by substituting equation (4) into (3), giving
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1
ˆ ˆ( ) (0)
2
T
f
f x f x
x
(5)
Through a new method for fitting a 3D quadratic function [14] to locate key points at the
location and scale of the central sample point, at the same time, the feature points that have low
contrast can be removed. In addition, the difference-of-Gaussian function will have a strong
response along edges, even if the location along the edge is poorly determined and therefore
unstable to small amounts of noise. And for stability and good ability to resist noise, it is not
sufficient to reject key points with low contrast. In order to overcome these problems and to
improve the stability, the Hessian matrix [15] was involved in, and considered its nature, the
edge response points of the DOG operator extreme will be removed.
2.3. Orientation Assignment
To achieve invariance to image rotation, the key point descriptor can be represented
relative to the orientation by assigning a consistent orientation to each key point based on local
image properties. SIFT assigns a local orientation by calculating the gradient magnitude of each
extreme point [16]. The scale of the key point is used to select the Gaussian smoothed image,
L, with the closest scale, so that all computations are performed in a scale-invariant manner. For
each image sample ( , )L x y at this scale, the gradient magnitude ( , )m x y and orientation ( , )x y
is recomputed using pixel differences:
22
))1,()1,(()),1(),1((),( yxLyxLyxLyxLyxm (6)
),1(),1(
)1,()1,(
tan),( 1
yxLyxL
yxLyxL
yx
(7)
An orientation histogram is formed from the gradient orientations of sample points within
a region around the feature point, Peaks in the orientation histogram correspond to dominant
directions of local gradients. The highest peak in the histogram is detected, and then any other
local peak that is within 80% of the highest peak is used to also create a keypoint with that
orientation [10]. Therefore, for locations with multiple peaks of similar magnitude, there will be
multiple keypoints created at the same location and scale but different orientations.
2.4. The Local Image Key Point Descriptor
Rotate the Gaussian image according to the current sample point's main orientation,
select the neighborhood area of the feature point after rotation as the object, and divide it into
4*4 sub areas, then calculate gradient histogram with 8 orientation bins in each for every sub
area, and as a result, the SIFT descriptor is formed from a 4*4*8=128 element feature vector
containing the values of all the orientation histogram entries [16]. By far, the SIFT feature vector
had removed the influence of geometrical deformation factor such as rotating and scale change,
etc. Finally, the feature vector is modified to reduce the effects of illumination change with
normalizing the vector to unit length.
3. MSER Elliptical Region Extraction and Orientation Calculation
3.1. MSER Elliptical Region Extraction
MSER algorithm is put forward by Mates. A MSER is carried out to obtain the final area
after selecting the appropriate threshold to an image to get connected components, and testing
the stability of the connected components.
For an image ( ),I x x , is a finite set of real functions, is a topology parameter,
and the element in the represents a pixel, in a word, is defined as. [1,2,......, ]n
n
domains 4 neighborhood and 8 neighborhood, but n=2 is not limited.
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( )S x is a level set of image ( )I x and the grayscale is not more than that in ( )I x ,
x .
)}()(:{)( xIyIyxS (8)
The sequence ),...,,( 21 nxxx is a connectivity sequence of pixels, such as ix and 1ix
are a four neighborhood or a 8 neighborhood, and 1,,1 ni . The connected component C
is a subset of , C , a couple of pixels
2
2,1 )( Cxx can be connected with a path in C. If
any connected component C contains C is equal to C, we called C the maximum connected
component. Extremal region R is defined as the maximum connected components of the level
set ( )S x . The collection of all extrema areas of the image I is represented by )(IR .
Among )(IR extremal regions, we are only interested in the special region which can
meet a certain steady standard as described below. The standard assumptions a extremum
zone R and )(RI is the maximum value of the image can be obtained in R:
)()( xISUPRI
Rx
(9)
Set 0 set R to contain the minimum extremely regions of R and its strength
larger than R at least,
})()(,),(|:min{|arg RIQIRQIRQQR (10)
As the same, set R to contain the minimum extremely regions of R and its strength
smaller than R at least,
})()(,),(|:min{|arg RIQIRQIRQQR (11)
Area transformation is defined:
||
||||
);(
R
RR
R
(12)
If the regional R is the regional minimum transform R is the most stable area. In the
following understanding: Whether any extremely region Q contains R or R contains Q, );( R
is smaller than );( Q . R and Q are two extreme regions, if QR and only if the another
extremism zone R meets QRR , then RR , saying R contains Q, and the definition
works only when is a finite set.
3.2. MSER Regional Fitting
After the completion of the image MSER area detection, it is essential to fit the rule area
to ellipse in order to facilitate the normalization and extracting a feature description. The
important information of a region and shape is its location, size and orientation, and the oval can
be more effective to reflect three types of information. The center of the ellipse as the center of
gravity of the MSER, the two axes of the ellipse passed through the center of gravity
respectively, Corresponding to the two axes of the second-order central moments in the major
axis minor axis direction respectively, the maximum and minimum (Hu proposed Image
Moments and Moment-based invariance systematically in 1962).
For an area of the image ),( yxI , its )( qp order two-dimensional geometric
moments defined as:
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dxdyyxIyxm qp
pq ),( 3,2,1,0, qp (13)
Geometric first moment
),(00 yxIm represents the area of a region (MSER),
equals to the number of element of which density value is 1.
Geometric first moment 01m and 10m :
),(01 yxxIm
,
),(10 yxyIm
(14)
The position of the center of gravity of the region can be got through standardized
calculation.
00
10
m
m
xc
, 00
01
m
m
yc
(15)
Center Second Moment is
0211
1120
2
U . We are more concerned about its center
matrix after calculating the center of gravity of the region, and we can get the so-called center
matrix with moving the origin point to the center of gravity and calculating, as shown below:
),()(
2
20 yxIxx c
),())((11 yxIyyxx cc
(16)
),()(
2
02 yxIyy c
As mentioned above, the long axial direction in the elliptical fitting region represented
the direction of the region, semimajor w and semiminor l represent the shape of the region, as
shown in Figure 1. These three parameters can be got by calculating the center second matrix
of the imageU .
00
1
m
w
00
2
m
l
(17)
)
2
arctan(
0220
11
Where 1 and 2 are two characteristic values of the Second Moment
0211
1120
U
,
and their specific value are as below:
2
]4)[()( 2
1
2
11
2
02200220
1
,
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2
]4)[()( 2
1
2
11
2
02200220
2
w
l
x
y
,
x,
y
Figure 1. Elliptic rotating schematic diagram
3.3. Orientation Assignment
Similar to the SIFT method of calculating the main direction, this paper also uses
gradient direction around the feature point to determine the main direction. Firstly we extract
ellipse area though section 3.1, and then normalize the elliptic area into a circular area (32*32
pixels), the normalized affine transformation relation is:
mxsAx ˆ ,
2
1
2RDA (18)
Among them, x is the coordinate of the measurement area, xˆ is the coordinate of
normalized area, D is the similarity transformation matrix of the covariance matrix generated
from ellipse fitting (real symmetric matrix).
Normalization into a circular region aims at making each pixel in elliptical region map to
the correct division unit when calculating the gradient distribution. And when calculating the
main direction of the normalized circular area, each pixel's gradient and phase of the circular
area should be calculated at first, and then weight the amplitude and the Gaussian function of
each pixel's phase, and overlay them onto the histogram according to the gradient direction. At
last, take the maximum value of phase histogram as the main direction of the current feature
point. When other directions are close to the direction of peak value, preserve it and identify it
as the second main direction. By assigning a stable main direction to each feature point, the
descriptor which generated from the main direction has invariance to the rotation of image.
It is noteworthy that, the significance of the normalized circular area and the meaning of
the SIFT circular region that determined by the scaling is not the same. Because the former is
obtained by conversion to the matrix of the shape which has a nature of affine invariant, and the
corresponding image region may not change at all after transformation, while in the SIFT the
corresponding two circular regions are determined by the scaling, there will be information
redundancy or insufficient information occasionally. Therefore, the main direction based on
normalized circular area that calculated in this paper will be more robust in affine transformation,
compared with original SIFT.
3.4. Key Point Descriptor
As section 2.4 shows, SIFT feature descriptor is a 128-element vector, this descriptor
describes the size of the 8 directions of the 16 sub-regions. Take it into account that the farther
the distance from the key point [13], the smaller the impact to the gradient information of feature
points. In this paper, the feature points of the area is divided into eight fan-sectors and using
Gaussian function to weight the gradient information field to construct a new SIFT feature
descriptor. Specific procedures are as follows:
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Taking feature point as the center, a circular region the radius of which is r is divided
into eight equiangular fan-shaped area, as shown in Figure 2. Lowe noted a 1616
neighborhood contains sufficient information without causing a large amount of calculation, and
thus the approximate size of the feature point neighborhood is used here to construct
characteristics descriptor, taking the radius of the circular area as 8.
Figure 2. Improved SIFT feature descriptor
Rotate the feature region by the main direction, as shown in Figure 4, after the rotation,
calculating eight direction gradient accumulated value of the sector region by a Gaussian
function to achieve the descriptor. First, calculate the size and direction of the gradient for each
pixel then stats gradient accumulated value of each fan-shaped area in eight directions. In order
to reduce the influence of the gradient of pixel away from the feature point to gradient
information of the feature point, using a Gaussian function to weight the gradient accumulated
value of the feature point. Then, mark the fan-shaped region in a clockwise direction with 1~8, in
the 1st region, 8 gradient accumulated value sort as the first to eight elements, in the 2nd
region, 8 gradient accumulated value sort as 9 to 16 elements, and so on. 8 sectors for 8 * 8
elements, the 1 * 64 vector is defined as a new characteristic descriptor of the feature point.
Finally, do a standard normalization processing to this vector to reduce the impact of
illumination change to feature descriptor.
New descriptor dimension is from 128 down to 64 dimensions compared with the
original characterization descriptor, further reducing the complexity of the algorithm and
matching time.
4. Experimental Results And Analysis
In order to verify the run rate of the intra-difference method and the improved SIFT
feature extraction algorithm that proposed in this paper, and the validity of the detection of
moving targets in complex environments (different lighting conditions, changes in the
background and particle noise interference),this chapter made a comparison between the
traditional SIFT features extraction [17] and the improved SIFT feature extraction through an
image sequence whose maximum size is 768*576 captured by a DH_CG400 capture card and
an analog camera. Three random collected pictures in strong, normal and weak light conditions
are showed in Figure 3.
Experimental results compared between the traditional SIFT feature extraction and
improved SIFT feature extraction such as Table 1.
As shown in Figure 4~7, the traditional SIFT can obtain not only characteristics from the
strong to the weak light case, but also a large number of other non-target feature vectors, which
will make the next step feature match longer time-consuming; Owing to using MSER algorithm
to generate the feature vector on the basis of the maximum stable region, improved SIFT can
not only get the target's eigenvectors under different lighting conditions, but also greatly reduce
the number of descriptors and thus greatly improved the speed of matching.
90
45
0
315
270
225
180
135
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(a) strong light condition (b) normal light condition (c) weak light condition
Figure 3. An image in different times under different light conditions
Table 1. The Experimental Data of the Different Images
Figure 4. Traditional SIFT feature extraction
Figure 5. Traditional SIFT feature extraction under affine conditions
Figure 6. Improved SIFT feature extraction
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Improved Characters Feature Extraction and Matching Algorithm Based on SIFT (Yueqiu Jiang)
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Figure 7. Improved SIFT feature extraction under affine conditions
5. Conclusion
In this paper, the MSER algorithm substitutes the DOG operator which used in
traditional SIFT algorithm, not only increasing the stability of the characteristics, but also
reducing the number of feature descriptor; followed with a fan-shaped sub-region instead of the
traditional square sub-region of the SIFT and the combination of Gaussian function to weighted
the gradient information field to construct the SIFT feature descriptor. Taking advantage of the
symmetry of the circular domain itself to STATS gradient orientation histogram, and using the
coordinate rotation could save the computational cost of image rotation, and reduce the number
of dimensions of the feature vector, and also has a certain recognition ability for the small target,
at the same time this algorithm can be combined with local information such as the edge further
enhanced the effectiveness of the algorithm. Experiments show that the algorithm not only has
translational invariance, scale invariance and rotational invariance, but also has affine
invariance and faster speed, and this algorithm can meet the requirements of real-time image
processing compared with the traditional SIFT algorithm. However, SIFT algorithm is prone to
using the multi-classification algorithm based on the minimum distance after detecting the
interest points, and that will affect the robustness of the algorithm, and in addition this, there are
many assumptions in the PCA model determines certain restrictions to this algorithm. Thus the
research on the more robust descriptors based on Hessian-Affine detector that replaced SIFT to
extract sub image area, as well as research on descriptor dimensionality reduction trial using
NLPCA will be the direction of future efforts.
Acknowledgements
This work is supported by Liaoning Province Colleges and Universities Excellent
Talents Support Program. (Grant No.LR201034), CALT Innovation Foundation (Grant
No.20130423), State Key Laboratory of Robotics Foundation, Shenyang Institute of Automation,
Chinese Academy of Sciences (Grant No.2012017) and also supported by the Liaoning
Province Educational Office Foundation of China (Grant No.L2011038).
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