Face recognition is one of the most challenging problems in the domain of image processing and machine vision. The face recognition system is critical when individuals have very similar biometric signature such as identical twins. In this paper, the facial area in an image is detected using AdaBoost approach. After that the facial area is divided into some local regions. Finally, new efficient facial-based identical twins feature extractor based on the geometric moment is applied into local regions of face image.The utilized geometric moment is Zernike Moment (ZM) as a feature extractor inside the local regions of facial area of identical twins images. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian Twin Society which contain scaled and rotated facial images of identical twins in different illuminations. The results prove the ability of proposed method to recognize a pair of identical twins.Also, results show that the proposed method is robust to rotation, scaling and changing illumination.
ZERNIKE MOMENT-BASED FEATURE EXTRACTION FOR FACIAL RECOGNITION OF IDENTICAL T...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
An efficient feature extraction method with pseudo zernike moment for facial ...ijcsity
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. Face recognition system is critical when individuals have very similar biometric signature such as
identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according
to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected
using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical
twins in different illuminations. The results prove the ability of proposed method to recognize a pair of
identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing
illumination.
LOCAL REGION PSEUDO-ZERNIKE MOMENT- BASED FEATURE EXTRACTION FOR FACIAL RECOG...aciijournal
In the domain of image processing, face recognition is one of the most well-known research field. When
humans have very similar biometric properties, such as identical twins, the face recognition system is
considered as a challengeable problem. In this paper, the AdaBoost method is utilized to detect the
facial area of input image.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
Farsi character recognition using new hybrid feature extraction methodsijcseit
Identification of visual words and writings has long been one of the most essential and the most attractive
operations in the field of image processing which has been studied since the last few decades and includes
security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the
field of identification of visual writings are very similar to each other for the most parts of their analysis,
and depending on the needs of the operational field have presented different feature extraction. Changes in
style of writing and font and turns of words and other issues are challenges of characters identifying
activity. In this study, a system of Persian character identification using independent orthogonal moment
that is Zernike Moment and Fourier-Mellin Moment has been used as feature extraction technique. The
values of Zernike Moments as characteristics independent of rotation have been used for classification
issues in the past and each of their real and imaginary components have been neglected individually and
with the phase coefficients, each of them will be changed by rotation. In this study, Zernike and Fourier-
Mellin Moments have been investigated to detect Persian characters in noisy and noise-free images. Also,
an improvement on the k-Nearest Neighbor (k-NN) classifier is proposed for character recognition. Using
the results comparison of the proposed method with current salient methods such as Back Propagation
(BP) and Radial Basis Function (RBF) neural networks in terms of feature extraction in words, it has been
shown that on the Hoda database, the proposed method reaches an acceptable detection rate (96/5%).
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.
Medoid based model for face recognition using eigen and fisher facesijscmcj
Biometric technologies have gained a remarkable impetus in high security applications. Various biometric modalities are widely being used these days. The need for unobtrusive biometric recognition can be fulfilled through Face recognition which is the most natural and non intrusive authentication system. However the vulnerability to changes owing to variations in face due to various factors like pose,
illumination, ageing, emotions, expressions etc make it necessary to have robust face recognition systems.
Various statistical models have been developed so far with varying degree of accuracy and efficiency. This
paper discusses a new approach to utilize Eigen face and Fisher face methodology by using medoid instead
of mean as a statistic in calculating the Eigen faces and Fisher faces. The method not only requires lesser training but also demonstrates better time efficiency and performance compared to the conventional method of using mean
ZERNIKE MOMENT-BASED FEATURE EXTRACTION FOR FACIAL RECOGNITION OF IDENTICAL T...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
An efficient feature extraction method with pseudo zernike moment for facial ...ijcsity
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. Face recognition system is critical when individuals have very similar biometric signature such as
identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according
to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected
using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical
twins in different illuminations. The results prove the ability of proposed method to recognize a pair of
identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing
illumination.
LOCAL REGION PSEUDO-ZERNIKE MOMENT- BASED FEATURE EXTRACTION FOR FACIAL RECOG...aciijournal
In the domain of image processing, face recognition is one of the most well-known research field. When
humans have very similar biometric properties, such as identical twins, the face recognition system is
considered as a challengeable problem. In this paper, the AdaBoost method is utilized to detect the
facial area of input image.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
Farsi character recognition using new hybrid feature extraction methodsijcseit
Identification of visual words and writings has long been one of the most essential and the most attractive
operations in the field of image processing which has been studied since the last few decades and includes
security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the
field of identification of visual writings are very similar to each other for the most parts of their analysis,
and depending on the needs of the operational field have presented different feature extraction. Changes in
style of writing and font and turns of words and other issues are challenges of characters identifying
activity. In this study, a system of Persian character identification using independent orthogonal moment
that is Zernike Moment and Fourier-Mellin Moment has been used as feature extraction technique. The
values of Zernike Moments as characteristics independent of rotation have been used for classification
issues in the past and each of their real and imaginary components have been neglected individually and
with the phase coefficients, each of them will be changed by rotation. In this study, Zernike and Fourier-
Mellin Moments have been investigated to detect Persian characters in noisy and noise-free images. Also,
an improvement on the k-Nearest Neighbor (k-NN) classifier is proposed for character recognition. Using
the results comparison of the proposed method with current salient methods such as Back Propagation
(BP) and Radial Basis Function (RBF) neural networks in terms of feature extraction in words, it has been
shown that on the Hoda database, the proposed method reaches an acceptable detection rate (96/5%).
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.
Medoid based model for face recognition using eigen and fisher facesijscmcj
Biometric technologies have gained a remarkable impetus in high security applications. Various biometric modalities are widely being used these days. The need for unobtrusive biometric recognition can be fulfilled through Face recognition which is the most natural and non intrusive authentication system. However the vulnerability to changes owing to variations in face due to various factors like pose,
illumination, ageing, emotions, expressions etc make it necessary to have robust face recognition systems.
Various statistical models have been developed so far with varying degree of accuracy and efficiency. This
paper discusses a new approach to utilize Eigen face and Fisher face methodology by using medoid instead
of mean as a statistic in calculating the Eigen faces and Fisher faces. The method not only requires lesser training but also demonstrates better time efficiency and performance compared to the conventional method of using mean
A Novel Mathematical Based Method for Generating Virtual Samples from a Front...CSCJournals
This paper deals with one sample face recognition which is a new challenging problem in pattern recognition. In the proposed method, the frontal 2D face image of each person divided to some sub-regions. After computing the 3D shape of each sub-region, a fusion scheme is applied on sub-regions to create a total 3D shape for whole face image. Then, 2D face image is added to the corresponding 3D shape to construct 3D face image. Finally by rotating the 3D face image, virtual samples with different views are generated. Experimental results on ORL dataset using nearest neighbor as classifier reveal an improvement about 5% in recognition rate for one sample per person by enlarging training set using generated virtual samples. Compared with other related works, the proposed method has the following advantages: 1) only one single frontal face is required for face recognition and the outputs are virtual images with variant views for each individual 2) need only 3 key points of face (eyes and nose) 3) 3D shape estimation for generating virtual samples is fully automatic and faster than other 3D reconstruction approaches 4) it is fully mathematical with no training phase and the estimated 3D model is unique for each individual.
In this paper person identification is done based on sets of facial images. Each facial image is considered as the scattered point of logistic regression. The vertical distance of scattered point of facial image and the regression line is considered as the parameter to determine whether the image is of same person or not. The ratio of Euclidian distance (in terms of number of pixel of gray scale image based on ‘imtool’ of Matlab 13.0) between nasal and eye points are determined. The variance of the ration is considered another parameter to identify a facial image. The concept is combined with ghost image of Principal Component Analysis; where the mean square error and signal to noise ratio (SNR) in dB is considered as the parameters of detection. The combination of three methods, enhance the degree of accuracy compared to individual one.
MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT POSITIONINGJaresJournal
The paper presents the Inverse Kinematics (IK) close form derivation steps using combination of analytical
and geometric techniques for the UR robot. The innovative application of this work is used in the precise
positioning of puncture robotics system. The end effector is a puncture needle guide tube, which needs
precise positioning over the puncture insertion point. The IK closed form solutions bring out maximum 8
solutions represents 8 different robot joints configurations. These multiple solutions are helpful in the
puncture robotics system, it allow doctors to choose the most suitable configuration during the operation.
Therefore the workspace becomes more adequate for the coexistence of human and robot. Moreover IK
closed form solutions are more precise in positioning for medical puncture surgery compared to other
numerical methods. We include a performance evaluation for both of the IK obtained by the closed form
solution and by a numerical method.
MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT POSITIONINGJaresJournal
The paper presents the Inverse Kinematics (IK) close form derivation steps using combination of analytical
and geometric techniques for the UR robot. The innovative application of this work is used in the precise
positioning of puncture robotics system. The end effector is a puncture needle guide tube, which needs
precise positioning over the puncture insertion point. The IK closed form solutions bring out maximum 8
solutions represents 8 different robot joints configurations. These multiple solutions are helpful in the
puncture robotics system, it allow doctors to choose the most suitable configuration during the operation.
Therefore the workspace becomes more adequate for the coexistence of human and robot. Moreover IK
closed form solutions are more precise in positioning for medical puncture surgery compared to other
numerical methods. We include a performance evaluation for both of the IK obtained by the closed form
solution and by a numerical method.
Face Detection for identification of people in Images of Internetijceronline
One method for searching the internet faces in images is proposed by using digital processing topological with descriptors. Location in real time with the development of a database that stores addresses of internet downloaded images, in which the search is done by text, but by finding facial image, is achieved. Face recognition in images of Internet has proved to be a difficult task, because the images vary considerably depending on viewpoint, illumination, expression, pose, accessories, etc. The descriptors for general information: containing low-level descriptors. Developments on face recognition systems have improved significantly since the first system; image analysis is a topic on which much emphasis is being given in order to identify parameters, visual features in the image that provide environment data that it is represented in the image, but without the intervention of a person. In this project raises its realization using the method of viola and jones as face descriptor. We can distinguish even different parts of the face such as eyes, eyebrows, nose and mouth.One method for searching faces in image taken from internet intends to use digital processing using topological descriptors. It is located the face in real time.
Reconstructing Vehicle License Plate Image from Low Resolution Images using N...CSCJournals
In this study, non-uniform interpolation method was adopted to reconstruct license plate image from a series of low resolution vehicle license plate images. Several image registration methods which were used to estimate the position and orientation differences between these low resolution images are tested in this study. It was found that the Fourier method is superior to other methods. The non-uniform interpolation method is then used to reconstruct vehicle license plate images from images with a character size as small as 3 × 6 pixels. Results show that although the number or character is still not easy to read, the reconstructed image shows a better readability than the original image. Keywords: image enhancement, image registration, license plate recognition.
FACE RECOGNITION USING DIFFERENT LOCAL FEATURES WITH DIFFERENT DISTANCE TECHN...IJCSEIT Journal
A face recognition system using different local features with different distance measures is proposed in this
paper. Proposed method is fast and gives accurate detection. Feature vector is based on Eigen values,
Eigen vectors, and diagonal vectors of sub images. Images are partitioned into sub images to detect local
features. Sub partitions are rearranged into vertically and horizontally matrices. Eigen values, Eigenvector
and diagonal vectors are computed for these matrices. Global feature vector is generated for face
recognition. Experiments are performed on benchmark face YALE database. Results indicate that the
proposed method gives better recognition performance in terms of average recognized rate and retrieval
time compared to the existing methods.
Iris Localization - a Biometric Approach Referring Daugman's AlgorithmEditor IJCATR
In general, there are many methods of biometric identification. But the Iris
recognition is most accurate and secure means of biometric identification. Iris has
many properties which makes it ideal biometric identification. There are many
methods used to identify the Iris location. To locate Iris many traditional methods are
used. In this we proposed such methods which can identify Iris Center(IC) as well as
localize its center. In this paper we are proposing a method which can use novel IC
localization method on the fact that the elliptical shape (ES) of Iris varies according to
the rotation of eye movement. In this paper various IC locations are generated and
stored in database. Finally the location of IC is detected by matching the ES of the Iris
of input eye image withes candidates in DB. In this paper we are comparing different
methods for Iris localization.
Face Alignment Using Active Shape Model And Support Vector MachineCSCJournals
The Active Shape Model (ASM) is one of the most popular local texture models for face alignment. It applies in many fields such as locating facial features in the image, face synthesis, etc. However, the experimental results show that the accuracy of the classical ASM for some applications is not high. This paper suggests some improvements on the classical ASM to increase the performance of the model in the application: face alignment. Four of our major improvements include: i) building a model combining Sobel filter and the 2-D profile in searching face in image; ii) applying Canny algorithm for the enhancement edge on image; iii) Support Vector Machine (SVM) is used to classify landmarks on face, in order to determine exactly location of these landmarks support for ASM; iv) automatically adjust 2-D profile in the multi-level model based on the size of the input image. The experimental results on CalTech face database and Technical University of Denmark database (imm_face) show that our proposed improvement leads to far better performance.
Extraction of texture features by using gabor filter in wheat crop disease de...eSAT Journals
Abstract
Like country India, there are so many people depending upon agriculture. In this area, many farmers don’t know about new
diseases which are impacting on their farm. As the disease changes, the disease control policy also changes. So many farmers
have very sharp observation on crop diseases, but whenever there is new diseases fall on crops then problems occur. Climate also
changes instantly many of times, because of such reasons farmers unable to understand various diseases.
If farmer unable to predict that diseases quickly then it will affect life of crops. Indirectly it gets affects on total productivity of
farm. As we are well known about that world facing lot of problems due rapid growth in population. So our goal is to increase
agricultural productivity using image processing technology which can help farmer in great extent [7].
In this research work, we are trying that crop disease using Artificial neural network (ANN) which work very effectively. First of
all, we have provided an digital image which is taken by digital camera. That image given to Gaussian filter firstly then
transferred to adaptive median filter to filter out noise present inside image. Gaussian filter removes Gaussian noise which is
present inside image. Adaptive noise filter removes impulsive noise which is present inside image. Also it will reduce distortions
which are present inside images. Then image transferred to segmentation part. In image segmentation we have choose CIELAB
color space method to extract color components properly. For segmentation we have used Gabor filter. After this we distinguish
crop diseases on the basis of texture features which are extracted by Gabor filter [6].
Key Words: Artificial Neural Networks, Image preprocessing, Image Acquisition, and Feature Extraction,
classification etc…
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.
FPGA ARCHITECTURE FOR FACIAL-FEATURES AND COMPONENTS EXTRACTIONijcseit
Several methods for detecting the face and extracting the facial features and components exist in the
literature. These methods are different in their complexity, performance, type and nature of the images and
the targeted application. The facial features and components are used in security applications, robotics and
assistance for the disabled. We use these components and characteristics to determine the state of alertness
and fatigue for medical diagnoses. In this work we use plain color background images whose color is
different from the skin and which contain a single face. We are interested in FPGA implementation of this
application. This implementation must meet two constraints, which are the execution time and the FPGA
resources. We have selected and have associated a face detection algorithm based on the skin detection
(using the RGB space) with a facial-feature extraction algorithm based on tracking the gradient and the
geometric model.
Development modeling methods of analysis and synthesis of fingerprint deforma...IJECEIAES
The current study is to develop modeling methods, analysis and synthesis of fingerprints deformations images and their application in problems of automatic fingerprint identification. In the introduction justified urgency of the problem, is given a brief description of thematic publications. In this study will review of modern technologies of biometric technologies and methods of biometric identification, the review of fingerprint identification systems, investigate for distorting factors. The influence of deformations is singled out, the causes of deformation of fingerprints are analyzed. The review of modern ways of the account and modeling of deformations in problems of automatic fingerprint identification is given. The scientific novelty of the work is the development of information technologies for the analysis and synthesis of deformations of fingerprint images. The practical value of the work in the application of the developed methods, algorithms and information technologies in fingerprints identification systems. In addition, it has been found that our paper "devoted to research methods and synthesis of the fingerprint deformations" is a more appropriate choice than other papers.
ZERNIKE MOMENT-BASED FEATURE EXTRACTION FOR FACIAL RECOGNITION OF IDENTICAL T...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
& Topics International Journal of Computer Science, Engineering and Informati...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
Local Region Pseudo-Zernike Moment- Based Feature Extraction for Facial Recog...aciijournal
In the domain of image processing, face recognition is one of the most well-known research field. When
humans have very similar biometric properties, such as identical twins, the face recognition system is
considered as a challengeable problem. In this paper, the AdaBoost method is utilized to detect the
facial area of input image. After that the facial area is divided into some local regions. Finally, new
efficient facial-based identical twins feature extractor based on the geometric moment is applied into
local regions of face image. The used feature extractor is Pseudo-Zernike Moment (PZM) which is
employed inside the local regions of facial area of identical twins images. To evaluate the proposed
method, two datasets, Twins Days Festival and Iranian Twin Society, are collected where the datasets
includes scaled and rotated facial images of identical twins in different illuminations. The experimental
results demonstrates the ability of proposed method to recognize a pair of identical twins in
different situations such as rotation, scaling and changing illumination
Local Region Pseudo-Zernike Moment- Based Feature Extraction for Facial Recog...aciijournal
In the domain of image processing, face recognition is one of the most well-known research field. When humans have very similar biometric properties, such as identical twins, the face recognition system is considered as a challengeable problem. In this paper, the AdaBoost method is utilized to detect the facial area of input image. After that the facial area is divided into some local regions. Finally, new efficient facial-based identical twins feature extractor based on the geometric moment is applied into local regions of face image. The used feature extractor is Pseudo-Zernike Moment (PZM) which is employed inside the local regions of facial area of identical twins images. To evaluate the proposed method, two datasets, Twins Days Festival and Iranian Twin Society, are collected where the datasets includes scaled and rotated facial images of identical twins in different illuminations. The experimental results demonstrates the ability of proposed method to recognize a pair of identical twins in different situations such as rotation, scaling and changing illumination
Character recognition is a new research field in the domain of pattern recognition which deals with the
style of writing. Some of the challengeable problems in character identification are changing in the style of
writing, font and turns of words and etc. In this paper, the goal is Persian character identification using
independent orthogonal moment as the feature extraction technique.The proposed feature extraction
method is the combination of Pseudo-Zernike Moment and Fourier-Mellin Moment called Pseudo-Zernike-
Mellin Moment to extract feature vector from Persian characters. The proposed character identification
system is evaluated on the HODA dataset and obtained 97.76% acceptance rate.
FARSI CHARACTER RECOGNITION USING NEW HYBRID FEATURE EXTRACTION METHODSijcseit
Identification of visual words and writings has long been one of the most essential and the most attractive
operations in the field of image processing which has been studied since the last few decades and includes
security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the
field of identification of visual writings are very similar to each other for the most parts of their analysis,
and depending on the needs of the operational field have presented different feature extraction. Changes in
style of writing and font and turns of words and other issues are challenges of characters identifying
activity. In this study, a system of Persian character identification using independent orthogonal moment
that is Zernike Moment and Fourier-Mellin Moment has been used as feature extraction technique. The
values of Zernike Moments as characteristics independent of rotation have been used for classification
issues in the past and each of their real and imaginary components have been neglected individually and
with the phase coefficients, each of them will be changed by rotation. In this study, Zernike and FourierMellin Moments have been investigated to detect Persian characters in noisy and noise-free images. Also,
an improvement on the k-Nearest Neighbor (k-NN) classifier is proposed for character recognition. Using
the results comparison of the proposed method with current salient methods such as Back Propagation
(BP) and Radial Basis Function (RBF) neural networks in terms of feature extraction in words, it has been
shown that on the Hoda database, the proposed method reaches an acceptable detection rate (96/5%).
International Journal of Computer Science, Engineering and Information Techno...ijcseit
Identification of visual words and writings has long been one of the most essential and the most attractive
operations in the field of image processing which has been studied since the last few decades and includes
security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the
field of identification of visual writings are very similar to each other for the most parts of their analysis,
and depending on the needs of the operational field have presented different feature extraction. Changes in
style of writing and font and turns of words and other issues are challenges of characters identifying
activity. In this study, a system of Persian character identification using independent orthogonal moment
that is Zernike Moment and Fourier-Mellin Moment has been used as feature extraction technique. The
values of Zernike Moments as characteristics independent of rotation have been used for classification
issues in the past and each of their real and imaginary components have been neglected individually and
with the phase coefficients, each of them will be changed by rotation. In this study, Zernike and FourierMellin
Moments have been investigated to detect Persian characters in noisy and noise-free images. Also,
an improvement on the k-Nearest Neighbor (k-NN) classifier is proposed for character recognition. Using
the results comparison of the proposed method with current salient methods such as Back Propagation
(BP) and Radial Basis Function (RBF) neural networks in terms of feature extraction in words, it has been
shown that on the Hoda database, the proposed method reaches an acceptable detection rate (96/5%).
Human’s facial parts extraction to recognize facial expressionijitjournal
Real-time facial expression analysis is an important yet challenging task in human computer interaction.
This paper proposes a real-time person independent facial expression recognition system using a
geometrical feature-based approach. The face geometry is extracted using the modified active shape
model. Each part of the face geometry is effectively represented by the Census Transformation (CT) based
feature histogram. The facial expression is classified by the SVM classifier with exponential chi-square
weighted merging kernel. The proposed method was evaluated on the JAFFE database and in real-world
environment. The experimental results show that the approach yields a high recognition rate and is
applicable in real-time facial expression analysis.
SYMMETRICAL WEIGHTED SUBSPACE HOLISTIC APPROACH FOR EXPRESSION RECOGNITIONijcsit
Human face expression is one of the cognitive activity or attribute to deliver the opinions to others.This paper mainly delivers the performance of appearance based holistic approach subspace methods based on Principal Component Analysis (PCA). In this work texture features are extracted from face images using Gabor filter. It was observed that extracted texture feature vector space has higher dimensional and has
more number of redundant contents. Hence training, testing and classification time becomes more. The expression recognition accuracy rate is also reduced. To overcome this problem Symmetrical Weighted 2DPCA (SW2DPCA) subspace method is introduced. Extracted feature vector space is projected in to subspace by using SW2DPCA method. By implementing weighted principles on odd and even symmetrical
decomposition space of training samples sets proposed method have been formed. Conventional PCA and 2DPCA method yields less recognition rate due to larger variations in expressions and light due to more number of feature space redundant variants. Proposed SW2DPCA method optimizes this problem by reducing redundant contents and discarding unequal variants. In this work a well known JAFFE databases
is used for experiments and tested with proposed SW2DPCA algorithm. From the experimental results it was found that facial recognition accuracy rate of GF+SW2DPCA based feature fusion subspace method has been increased to 95.24% compared to 2DPCA method.
A Novel Mathematical Based Method for Generating Virtual Samples from a Front...CSCJournals
This paper deals with one sample face recognition which is a new challenging problem in pattern recognition. In the proposed method, the frontal 2D face image of each person divided to some sub-regions. After computing the 3D shape of each sub-region, a fusion scheme is applied on sub-regions to create a total 3D shape for whole face image. Then, 2D face image is added to the corresponding 3D shape to construct 3D face image. Finally by rotating the 3D face image, virtual samples with different views are generated. Experimental results on ORL dataset using nearest neighbor as classifier reveal an improvement about 5% in recognition rate for one sample per person by enlarging training set using generated virtual samples. Compared with other related works, the proposed method has the following advantages: 1) only one single frontal face is required for face recognition and the outputs are virtual images with variant views for each individual 2) need only 3 key points of face (eyes and nose) 3) 3D shape estimation for generating virtual samples is fully automatic and faster than other 3D reconstruction approaches 4) it is fully mathematical with no training phase and the estimated 3D model is unique for each individual.
In this paper person identification is done based on sets of facial images. Each facial image is considered as the scattered point of logistic regression. The vertical distance of scattered point of facial image and the regression line is considered as the parameter to determine whether the image is of same person or not. The ratio of Euclidian distance (in terms of number of pixel of gray scale image based on ‘imtool’ of Matlab 13.0) between nasal and eye points are determined. The variance of the ration is considered another parameter to identify a facial image. The concept is combined with ghost image of Principal Component Analysis; where the mean square error and signal to noise ratio (SNR) in dB is considered as the parameters of detection. The combination of three methods, enhance the degree of accuracy compared to individual one.
MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT POSITIONINGJaresJournal
The paper presents the Inverse Kinematics (IK) close form derivation steps using combination of analytical
and geometric techniques for the UR robot. The innovative application of this work is used in the precise
positioning of puncture robotics system. The end effector is a puncture needle guide tube, which needs
precise positioning over the puncture insertion point. The IK closed form solutions bring out maximum 8
solutions represents 8 different robot joints configurations. These multiple solutions are helpful in the
puncture robotics system, it allow doctors to choose the most suitable configuration during the operation.
Therefore the workspace becomes more adequate for the coexistence of human and robot. Moreover IK
closed form solutions are more precise in positioning for medical puncture surgery compared to other
numerical methods. We include a performance evaluation for both of the IK obtained by the closed form
solution and by a numerical method.
MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT POSITIONINGJaresJournal
The paper presents the Inverse Kinematics (IK) close form derivation steps using combination of analytical
and geometric techniques for the UR robot. The innovative application of this work is used in the precise
positioning of puncture robotics system. The end effector is a puncture needle guide tube, which needs
precise positioning over the puncture insertion point. The IK closed form solutions bring out maximum 8
solutions represents 8 different robot joints configurations. These multiple solutions are helpful in the
puncture robotics system, it allow doctors to choose the most suitable configuration during the operation.
Therefore the workspace becomes more adequate for the coexistence of human and robot. Moreover IK
closed form solutions are more precise in positioning for medical puncture surgery compared to other
numerical methods. We include a performance evaluation for both of the IK obtained by the closed form
solution and by a numerical method.
Face Detection for identification of people in Images of Internetijceronline
One method for searching the internet faces in images is proposed by using digital processing topological with descriptors. Location in real time with the development of a database that stores addresses of internet downloaded images, in which the search is done by text, but by finding facial image, is achieved. Face recognition in images of Internet has proved to be a difficult task, because the images vary considerably depending on viewpoint, illumination, expression, pose, accessories, etc. The descriptors for general information: containing low-level descriptors. Developments on face recognition systems have improved significantly since the first system; image analysis is a topic on which much emphasis is being given in order to identify parameters, visual features in the image that provide environment data that it is represented in the image, but without the intervention of a person. In this project raises its realization using the method of viola and jones as face descriptor. We can distinguish even different parts of the face such as eyes, eyebrows, nose and mouth.One method for searching faces in image taken from internet intends to use digital processing using topological descriptors. It is located the face in real time.
Reconstructing Vehicle License Plate Image from Low Resolution Images using N...CSCJournals
In this study, non-uniform interpolation method was adopted to reconstruct license plate image from a series of low resolution vehicle license plate images. Several image registration methods which were used to estimate the position and orientation differences between these low resolution images are tested in this study. It was found that the Fourier method is superior to other methods. The non-uniform interpolation method is then used to reconstruct vehicle license plate images from images with a character size as small as 3 × 6 pixels. Results show that although the number or character is still not easy to read, the reconstructed image shows a better readability than the original image. Keywords: image enhancement, image registration, license plate recognition.
FACE RECOGNITION USING DIFFERENT LOCAL FEATURES WITH DIFFERENT DISTANCE TECHN...IJCSEIT Journal
A face recognition system using different local features with different distance measures is proposed in this
paper. Proposed method is fast and gives accurate detection. Feature vector is based on Eigen values,
Eigen vectors, and diagonal vectors of sub images. Images are partitioned into sub images to detect local
features. Sub partitions are rearranged into vertically and horizontally matrices. Eigen values, Eigenvector
and diagonal vectors are computed for these matrices. Global feature vector is generated for face
recognition. Experiments are performed on benchmark face YALE database. Results indicate that the
proposed method gives better recognition performance in terms of average recognized rate and retrieval
time compared to the existing methods.
Iris Localization - a Biometric Approach Referring Daugman's AlgorithmEditor IJCATR
In general, there are many methods of biometric identification. But the Iris
recognition is most accurate and secure means of biometric identification. Iris has
many properties which makes it ideal biometric identification. There are many
methods used to identify the Iris location. To locate Iris many traditional methods are
used. In this we proposed such methods which can identify Iris Center(IC) as well as
localize its center. In this paper we are proposing a method which can use novel IC
localization method on the fact that the elliptical shape (ES) of Iris varies according to
the rotation of eye movement. In this paper various IC locations are generated and
stored in database. Finally the location of IC is detected by matching the ES of the Iris
of input eye image withes candidates in DB. In this paper we are comparing different
methods for Iris localization.
Face Alignment Using Active Shape Model And Support Vector MachineCSCJournals
The Active Shape Model (ASM) is one of the most popular local texture models for face alignment. It applies in many fields such as locating facial features in the image, face synthesis, etc. However, the experimental results show that the accuracy of the classical ASM for some applications is not high. This paper suggests some improvements on the classical ASM to increase the performance of the model in the application: face alignment. Four of our major improvements include: i) building a model combining Sobel filter and the 2-D profile in searching face in image; ii) applying Canny algorithm for the enhancement edge on image; iii) Support Vector Machine (SVM) is used to classify landmarks on face, in order to determine exactly location of these landmarks support for ASM; iv) automatically adjust 2-D profile in the multi-level model based on the size of the input image. The experimental results on CalTech face database and Technical University of Denmark database (imm_face) show that our proposed improvement leads to far better performance.
Extraction of texture features by using gabor filter in wheat crop disease de...eSAT Journals
Abstract
Like country India, there are so many people depending upon agriculture. In this area, many farmers don’t know about new
diseases which are impacting on their farm. As the disease changes, the disease control policy also changes. So many farmers
have very sharp observation on crop diseases, but whenever there is new diseases fall on crops then problems occur. Climate also
changes instantly many of times, because of such reasons farmers unable to understand various diseases.
If farmer unable to predict that diseases quickly then it will affect life of crops. Indirectly it gets affects on total productivity of
farm. As we are well known about that world facing lot of problems due rapid growth in population. So our goal is to increase
agricultural productivity using image processing technology which can help farmer in great extent [7].
In this research work, we are trying that crop disease using Artificial neural network (ANN) which work very effectively. First of
all, we have provided an digital image which is taken by digital camera. That image given to Gaussian filter firstly then
transferred to adaptive median filter to filter out noise present inside image. Gaussian filter removes Gaussian noise which is
present inside image. Adaptive noise filter removes impulsive noise which is present inside image. Also it will reduce distortions
which are present inside images. Then image transferred to segmentation part. In image segmentation we have choose CIELAB
color space method to extract color components properly. For segmentation we have used Gabor filter. After this we distinguish
crop diseases on the basis of texture features which are extracted by Gabor filter [6].
Key Words: Artificial Neural Networks, Image preprocessing, Image Acquisition, and Feature Extraction,
classification etc…
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.
FPGA ARCHITECTURE FOR FACIAL-FEATURES AND COMPONENTS EXTRACTIONijcseit
Several methods for detecting the face and extracting the facial features and components exist in the
literature. These methods are different in their complexity, performance, type and nature of the images and
the targeted application. The facial features and components are used in security applications, robotics and
assistance for the disabled. We use these components and characteristics to determine the state of alertness
and fatigue for medical diagnoses. In this work we use plain color background images whose color is
different from the skin and which contain a single face. We are interested in FPGA implementation of this
application. This implementation must meet two constraints, which are the execution time and the FPGA
resources. We have selected and have associated a face detection algorithm based on the skin detection
(using the RGB space) with a facial-feature extraction algorithm based on tracking the gradient and the
geometric model.
Development modeling methods of analysis and synthesis of fingerprint deforma...IJECEIAES
The current study is to develop modeling methods, analysis and synthesis of fingerprints deformations images and their application in problems of automatic fingerprint identification. In the introduction justified urgency of the problem, is given a brief description of thematic publications. In this study will review of modern technologies of biometric technologies and methods of biometric identification, the review of fingerprint identification systems, investigate for distorting factors. The influence of deformations is singled out, the causes of deformation of fingerprints are analyzed. The review of modern ways of the account and modeling of deformations in problems of automatic fingerprint identification is given. The scientific novelty of the work is the development of information technologies for the analysis and synthesis of deformations of fingerprint images. The practical value of the work in the application of the developed methods, algorithms and information technologies in fingerprints identification systems. In addition, it has been found that our paper "devoted to research methods and synthesis of the fingerprint deformations" is a more appropriate choice than other papers.
ZERNIKE MOMENT-BASED FEATURE EXTRACTION FOR FACIAL RECOGNITION OF IDENTICAL T...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
& Topics International Journal of Computer Science, Engineering and Informati...ijcseit
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed
according to geometric moment. The utilized geometric moment is Zernike Moment (ZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area in an image is detected using
AdaBoost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian
Twin Society which contain scaled and rotated facial images of identical twins in different illuminations.
The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show
that the proposed method is robust to rotation, scaling and changing illumination.
Local Region Pseudo-Zernike Moment- Based Feature Extraction for Facial Recog...aciijournal
In the domain of image processing, face recognition is one of the most well-known research field. When
humans have very similar biometric properties, such as identical twins, the face recognition system is
considered as a challengeable problem. In this paper, the AdaBoost method is utilized to detect the
facial area of input image. After that the facial area is divided into some local regions. Finally, new
efficient facial-based identical twins feature extractor based on the geometric moment is applied into
local regions of face image. The used feature extractor is Pseudo-Zernike Moment (PZM) which is
employed inside the local regions of facial area of identical twins images. To evaluate the proposed
method, two datasets, Twins Days Festival and Iranian Twin Society, are collected where the datasets
includes scaled and rotated facial images of identical twins in different illuminations. The experimental
results demonstrates the ability of proposed method to recognize a pair of identical twins in
different situations such as rotation, scaling and changing illumination
Local Region Pseudo-Zernike Moment- Based Feature Extraction for Facial Recog...aciijournal
In the domain of image processing, face recognition is one of the most well-known research field. When humans have very similar biometric properties, such as identical twins, the face recognition system is considered as a challengeable problem. In this paper, the AdaBoost method is utilized to detect the facial area of input image. After that the facial area is divided into some local regions. Finally, new efficient facial-based identical twins feature extractor based on the geometric moment is applied into local regions of face image. The used feature extractor is Pseudo-Zernike Moment (PZM) which is employed inside the local regions of facial area of identical twins images. To evaluate the proposed method, two datasets, Twins Days Festival and Iranian Twin Society, are collected where the datasets includes scaled and rotated facial images of identical twins in different illuminations. The experimental results demonstrates the ability of proposed method to recognize a pair of identical twins in different situations such as rotation, scaling and changing illumination
Character recognition is a new research field in the domain of pattern recognition which deals with the
style of writing. Some of the challengeable problems in character identification are changing in the style of
writing, font and turns of words and etc. In this paper, the goal is Persian character identification using
independent orthogonal moment as the feature extraction technique.The proposed feature extraction
method is the combination of Pseudo-Zernike Moment and Fourier-Mellin Moment called Pseudo-Zernike-
Mellin Moment to extract feature vector from Persian characters. The proposed character identification
system is evaluated on the HODA dataset and obtained 97.76% acceptance rate.
FARSI CHARACTER RECOGNITION USING NEW HYBRID FEATURE EXTRACTION METHODSijcseit
Identification of visual words and writings has long been one of the most essential and the most attractive
operations in the field of image processing which has been studied since the last few decades and includes
security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the
field of identification of visual writings are very similar to each other for the most parts of their analysis,
and depending on the needs of the operational field have presented different feature extraction. Changes in
style of writing and font and turns of words and other issues are challenges of characters identifying
activity. In this study, a system of Persian character identification using independent orthogonal moment
that is Zernike Moment and Fourier-Mellin Moment has been used as feature extraction technique. The
values of Zernike Moments as characteristics independent of rotation have been used for classification
issues in the past and each of their real and imaginary components have been neglected individually and
with the phase coefficients, each of them will be changed by rotation. In this study, Zernike and FourierMellin Moments have been investigated to detect Persian characters in noisy and noise-free images. Also,
an improvement on the k-Nearest Neighbor (k-NN) classifier is proposed for character recognition. Using
the results comparison of the proposed method with current salient methods such as Back Propagation
(BP) and Radial Basis Function (RBF) neural networks in terms of feature extraction in words, it has been
shown that on the Hoda database, the proposed method reaches an acceptable detection rate (96/5%).
International Journal of Computer Science, Engineering and Information Techno...ijcseit
Identification of visual words and writings has long been one of the most essential and the most attractive
operations in the field of image processing which has been studied since the last few decades and includes
security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the
field of identification of visual writings are very similar to each other for the most parts of their analysis,
and depending on the needs of the operational field have presented different feature extraction. Changes in
style of writing and font and turns of words and other issues are challenges of characters identifying
activity. In this study, a system of Persian character identification using independent orthogonal moment
that is Zernike Moment and Fourier-Mellin Moment has been used as feature extraction technique. The
values of Zernike Moments as characteristics independent of rotation have been used for classification
issues in the past and each of their real and imaginary components have been neglected individually and
with the phase coefficients, each of them will be changed by rotation. In this study, Zernike and FourierMellin
Moments have been investigated to detect Persian characters in noisy and noise-free images. Also,
an improvement on the k-Nearest Neighbor (k-NN) classifier is proposed for character recognition. Using
the results comparison of the proposed method with current salient methods such as Back Propagation
(BP) and Radial Basis Function (RBF) neural networks in terms of feature extraction in words, it has been
shown that on the Hoda database, the proposed method reaches an acceptable detection rate (96/5%).
Human’s facial parts extraction to recognize facial expressionijitjournal
Real-time facial expression analysis is an important yet challenging task in human computer interaction.
This paper proposes a real-time person independent facial expression recognition system using a
geometrical feature-based approach. The face geometry is extracted using the modified active shape
model. Each part of the face geometry is effectively represented by the Census Transformation (CT) based
feature histogram. The facial expression is classified by the SVM classifier with exponential chi-square
weighted merging kernel. The proposed method was evaluated on the JAFFE database and in real-world
environment. The experimental results show that the approach yields a high recognition rate and is
applicable in real-time facial expression analysis.
SYMMETRICAL WEIGHTED SUBSPACE HOLISTIC APPROACH FOR EXPRESSION RECOGNITIONijcsit
Human face expression is one of the cognitive activity or attribute to deliver the opinions to others.This paper mainly delivers the performance of appearance based holistic approach subspace methods based on Principal Component Analysis (PCA). In this work texture features are extracted from face images using Gabor filter. It was observed that extracted texture feature vector space has higher dimensional and has
more number of redundant contents. Hence training, testing and classification time becomes more. The expression recognition accuracy rate is also reduced. To overcome this problem Symmetrical Weighted 2DPCA (SW2DPCA) subspace method is introduced. Extracted feature vector space is projected in to subspace by using SW2DPCA method. By implementing weighted principles on odd and even symmetrical
decomposition space of training samples sets proposed method have been formed. Conventional PCA and 2DPCA method yields less recognition rate due to larger variations in expressions and light due to more number of feature space redundant variants. Proposed SW2DPCA method optimizes this problem by reducing redundant contents and discarding unequal variants. In this work a well known JAFFE databases
is used for experiments and tested with proposed SW2DPCA algorithm. From the experimental results it was found that facial recognition accuracy rate of GF+SW2DPCA based feature fusion subspace method has been increased to 95.24% compared to 2DPCA method.
Improvement of the Recognition Rate by Random ForestIJERA Editor
In this paper; we introduce a system of automatic recognition of characters based on the Random Forest Method in non-constrictive pictures that are stemmed from the terminals Mobile phone. After doing some pretreatments on the picture, the text is segmented into lines and then into characters. In the stage of characteristics extraction, we are representing the input data into the vector of primitives of the zoning types, of diagonal, horizontal and of the Zernike moment. These characteristics are linked to pixels’ densities and they are extracted on binary pictures. In the classification stage, we examine four classification methods with two different classifiers types namely the multi-layer perceptron (MLP) and the Random Forest method. After some checking tests, the system of learning and recognition which is based on the Random Forest has shown a good performance on a basis of 100 models of pictures
Improvement oh the recognition rate by random forestYoussef Rachidi
In this paper; we introduce a system of automatic recognition of characters based on the Random Forest Method in non-constrictive pictures that are stemmed from the terminals Mobile phone. After doing some pretreatments on the picture, the text is segmented into lines and then into characters. In the stage of characteristics extraction, we are representing the input data into the vector of primitives of the zoning types, of diagonal, horizontal and of the Zernike moment. These characteristics are linked to pixels’ densities and they are extracted on binary pictures. In the classification stage, we examine four classification methods with two different classifiers types namely the multi-layer perceptron (MLP) and the Random Forest method. After some checking tests, the system of learning and recognition which is based on the Random Forest has shown a good performance on a basis of 100 models of pictures.
Realtime human face tracking and recognition system on uncontrolled environmentIJECEIAES
Recently, one of the most important biometrics is that automatically recognized human faces are based on dynamic facial images with different rotations and backgrounds. This paper presents a real-time system for human face tracking and recognition with various expressions of the face, poses, and rotations in an uncontrolled environment (dynamic background). Many steps are achieved in this paper to enhance, detect, and recognize the faces from the image frame taken by web-camera. The system has three steps: the first is to detect the face, Viola-Jones algorithm is used to achieve this purpose for frontal and profile face detection. In the second step, the color space algorithm is used to track the detected face from the previous step. The third step, principal component analysis (eigenfaces) algorithm is used to recognize faces. The result shows the effectiveness and robustness depending on the training and testing results. The real-time system result is compared with the results of the previous papers and gives a success, effectiveness, and robustness recognition rate of 91.12% with a low execution time. However, the execution time is not fixed due depending on the frame background and specification of the web camera and computer.
Independent Component Analysis of Edge Information for Face RecognitionCSCJournals
In this paper we address the problem of face recognition using edge information as independent components. The edge information is obtained by using Laplacian of Gaussian (LoG) and Canny edge detection methods then preprocessing is done by using Principle Component analysis (PCA) before applying the Independent Component Analysis (ICA) algorithm for training of images. The independent components obtained by ICA algorithm are used as feature vectors for classification. The Euclidean distance and Mahalanobis distance classifiers are used for testing of images. The algorithm is tested on two different databases of face images for variation in illumination and facial poses up to 180 degree rotation angle.
In this paper, we present an automatic application of 3D face recognition system using geodesic distance in Riemannian geometry. We consider, in this approach, the three dimensional face images as residing in Riemannian manifold and we compute the geodesic distance using the Jacobi iterations as a solution of the Eikonal equation. The problem of solving the Eikonal equation, unstructured simplified meshes of 3D face surface, such as tetrahedral and triangles are important for accurately modeling material interfaces and curved domains, which are approximations to curved surfaces in R3. In the classifying steps, we use: Neural Networks (NN), K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). To test this method and evaluate its performance, a simulation series of experiments were performed on 3D Shape REtrieval Contest 2008 database (SHREC2008).
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.
A study of techniques for facial detection and expression classificationIJCSES Journal
Automatic recognition of facial expressions is an important component for human-machine interfaces. It
has lot of attraction in research area since 1990's.Although humans recognize face without effort or
delay, recognition by a machine is still a challenge. Some of its challenges are highly dynamic in their
orientation, lightening, scale, facial expression and occlusion. Applications are in the fields like user
authentication, person identification, video surveillance, information security, data privacy etc. The
various approaches for facial recognition are categorized into two namely holistic based facial
recognition and feature based facial recognition. Holistic based treat the image data as one entity without
isolating different region in the face where as feature based methods identify certain points on the face
such as eyes, nose and mouth etc. In this paper, facial expression recognition is analyzed with various
methods of facial detection,facial feature extraction and classification.
International Journal of Computer Science, Engineering and Information Techno...IJCSEIT Journal
Several methods for detecting the face and extracting the facial features and components exist in the
literature. These methods are different in their complexity, performance, type and nature of the images and
the targeted application. The facial features and components are used in security applications, robotics and
assistance for the disabled. We use these components and characteristics to determine the state of alertness
and fatigue for medical diagnoses. In this work we use plain color background images whose color is
different from the skin and which contain a single face. We are interested in FPGA implementation of this
application. This implementation must meet two constraints, which are the execution time and the FPGA
resources. We have selected and have associated a face detection algorithm based on the skin detection
(using the RGB space) with a facial-feature extraction algorithm based on tracking the gradient and the
geometric model.
National Flags Recognition Based on Principal Component Analysisijtsrd
Recognizing an unknown flag in a scene is challenging due to the diversity of the data and to the complexity of the identification process. And flags are associated with geographical regions, countries and nations. But flag identification of different countries is a challenging and difficult task. Recognition of an unknown flag image in a scene is challenging due to the diversity of the data and to the complexity of the identification process. The aim of the study is to propose a feature extraction based recognition system for Myanmar's national flag. Image features are acquired from the region and state of flags which are identified by using principal component analysis PCA . PCA is a statistical approach used for reducing the number of features in National flags recognition system. Soe Moe Myint | Moe Moe Myint | Aye Aye Cho "National Flags Recognition Based on Principal Component Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26775.pdfPaper URL: https://www.ijtsrd.com/other-scientific-research-area/other/26775/national-flags-recognition-based-on-principal-component-analysis/soe-moe-myint
THE PRESSURE SIGNAL CALIBRATION TECHNOLOGY OF THE COMPREHENSIVE TEST SYSTEMieijjournal
The pressure signal calibration technology of the comprehensive test system which involved pressure
sensors was studied in this paper. The melioration of pressure signal calibration methods was elaborated.
Compared with the calibration methods in the lab and after analyzing the relevant problems,the
calibration technology online was achieved. The test datum and reasons of measuring error analyzed,the
uncertainty evaluation was given and then this calibration method was proved to be feasible and accurate.
8 th International Conference on Education (EDU 2023)ieijjournal
8th International Conference on Education (EDU 2023) will provide an excellent
international forum for sharing knowledge and results in theory, methodology and
applications impacts and challenges of education. The conference documents practical and
theoretical results which make a fundamental contribution for the development of
Educational research. The goal of this conference is to bring together researchers and
practitioners from academia and industry to focus on Educational advancements and
establishing new collaborations in these areas. Original research papers, state-of-the-art
reviews are invited for publication in all areas of Education
Informatics Engineering, an International Journal (IEIJ)ieijjournal
Informatics is a rapidly developing the field. The study of informatics involves human-computer
interaction and how an interface can be built to maximize user efficiency. Due to the growth in IT,
individuals and organizations increasingly process information digitally. This has led to the study of
informatics to solve privacy, security, healthcare, education, poverty, and challenges in our environment.
The Informatics Engineering, an International Journal (IEIJ) is an open access peer-reviewed journal that
publishes articles which contribute new results in all areas of Informatics. The goal of this journal is to
bring together researchers and practitioners from academia and industry to focus on the human use of
computing fields such as communication, mathematics, multimedia, and human-computer interaction
design and establishing new collaborations in these areas.
Big data is a prominent term which characterizes the improvement and availability of data in all three
formats like structure, unstructured and semi formats. Structure data is located in a fixed field of a record
or file and it is present in the relational data bases and spreadsheets whereas an unstructured data file
includes text and multimedia contents. The primary objective of this big data concept is to describe the
extreme volume of data sets i.e. both structured and unstructured. It is further defined with three “V”
dimensions namely Volume, Velocity and Variety, and two more “V” also added i.e. Value and Veracity.
Volume denotes the size of data, Velocity depends upon the speed of the data processing, Variety is
described with the types of the data, Value which derives the business value and Veracity describes about
the quality of the data and data understandability. Nowadays, big data has become unique and preferred
research areas in the field of computer science. Many open research problems are available in big data
and good solutions also been proposed by the researchers even though there is a need for development of
many new techniques and algorithms for big data analysis in order to get optimal solutions. In this paper,
a detailed study about big data, its basic concepts, history, applications, technique, research issues and
tools are discussed.
LOW POWER SI CLASS E POWER AMPLIFIER AND RF SWITCH FOR HEALTH CAREieijjournal
This research was to design a 2.4 GHz class E Power Amplifier (PA) for health care, with 0.18um
Semiconductor Manufacturing International Corporation CMOS technology by using Cadence software.
And also RF switch was designed at cadence software with power Jazz 180nm SOI process. The ultimate
goal for such application is to reach high performance and low cost, and between high performance and
low power consumption design. This paper introduces the design of a 2.4GHz class E power amplifier and
RF switch design. PA consists of cascade stage with negative capacitance. This power amplifier can
transmit 16dBm output power to a 50Ω load. The performance of the power amplifier and switch meet the
specification requirements of the desired
PRACTICE OF CALIBRATION TECHNOLOGY FOR THE SPECIAL TEST EQUIPMENT ieijjournal
For the issues encountered in the special test equipment calibration work, based on the characteristics of
special test equipment, the calibration point selection,classification of calibration parameters and
calibration method of special test equipment are briefly introduced in this paper, at the same time, the
preparation and management requirements of calibration specification are described.
8th International Conference on Signal, Image Processing and Embedded Systems...ieijjournal
8th International Conference on Signal, Image Processing and Embedded Systems (SIGEM 2022) is a forum for presenting new advances and research results in the fields of Digital Image Processing and Embedded Systems.
Informatics Engineering, an International Journal (IEIJ)ieijjournal
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An Efficient Feature Extraction Method With Local Region Zernike Moment for Facial Recognition of Identical Twins
1. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
1
AN EFFICIENT FEATURE EXTRACTION METHOD WITH
LOCAL REGION ZERNIKE MOMENT FOR FACIAL
RECOGNITION OF IDENTICAL TWINS
Zahra Ahmadi-Dastjerdi1
and Karim Faez2
1
Department of Electrical,Computer and Biomedical Engineering, Qazvin branch, Islamic
Azad University, Qazvin, Iran
2
Department of Electrical Engineering, Amirkabir University of Technology, Tehran,
Iran
ABSTRACT
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. The face recognition system is critical when individuals have very similar biometric signature such
as identical twins. In this paper, the facial area in an image is detected using AdaBoost approach. After
that the facial area is divided into some local regions. Finally, new efficient facial-based identical twins
feature extractor based on the geometric moment is applied into local regions of face image.The utilized
geometric moment is Zernike Moment (ZM) as a feature extractor inside the local regions of facial area of
identical twins images. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled and rotated facial images of identical twins in different
illuminations. The results prove the ability of proposed method to recognize a pair of identical twins.Also,
results show that the proposed method is robust to rotation, scaling and changing illumination.
KEYWORDS
Face Recognition,Identical Twins,Invariant Moment, Zernike Moment
1. INTRODUCTION
Human face is considered as a suitable property to identify people from his (her) image. Along
with this property, recognition of facial of identical twin is one of the most challenging problems
in pattern recognition applications because of the similarity between the pair of twin.
In the domain of facial identical twins recognition, previous works are listed as: in[12], Klare and
Jain introduced a face detection algorithm which includes three levels. In the first level, an overall
appearance of the face is constructed; in the second level, exact geometric and structural
embedment of face with differentiating between two similar faces are performed; and finally, the
third level consists of process of skin disorders such as wounds, and so on. Sun et al. [16] utilized
Cognitec FaceVACS system to recognize identical twins from CASIA Multimodal Biometrics
Database and they obtained the true accept rate of approximately 90% at a false accept rate
greater than 10%. Park et al.[14] proposed an identical twins recognition algorithm that consists
of three steps: in first step, the proposed method consists of face images which are marked using
normal geometric methods; in the second step, the Euclidean distance between a pair of markers
are measured and compared; and the final step involves finding the strong similarity on the
2. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
2
marked regions. Srinivas et al. [15] studied on distinguishing of twins using marks on the face
image. Martin et al. [3] employed DNA approach to recognize identical twins.
In this paper, we study on a pair of facial images in order to determine whether the images belong
to the same person or to a pair of identical twin. For this purpose, we propose the geometric
moments to extract feature vector from facial images of twins to recognize identical twins.
This paper is organized as follow: feature extraction step of a face recognition system
isintroduced in Section 2. The proposed method is presented in Section 3. Experimentalresults are
described in Section 4 and the paper will be concluded in Section 5.
2. FEATURE EXTRACTION
Each face detection system contains four steps: pre-processing, face localization, feature
extraction and classification. Feature extraction refers to the extraction of useful information from
raw data so that they are suitable for the classification process. The feature extraction stage is
characterized by a series of input patterns. The major problem of feature extraction is that it
depends on application and feature extraction methods are not public.
Feature extraction methods can be divided into two majors: structural features and statistical
features [11][19]. The first group is based on local structure of image. In other words, the
structural features deals with local data. Facial change or change in environmental conditions is
the major problem for the structural features [7].
In the statistics-based feature extraction techniques, global data is employed to create a set of
feature vector elements in order to perform recognition. A mixture of irrelevant data, which are
usually part of a facial image, may result in an incorrect set of feature vector elements. Therefore,
data that are irrelevant to facial portion such as hair, shoulders, and background should be is
regarded in the feature extraction phase [10].The statistics-based feature extraction techniques are
Principle Component Analysis (PCA), Legender Moment (LM) [13] and Zernike Moments (ZM)
[20]. Legendre functions are Legendre differential equation. The main advantage is that Legendre
moments like Legendre basis functions are orthogonal. Legendre moments are independent of
each other and are free of data redundancy.In this study, we use ZM to recognize identical twins
that are presented in the next Section.
3. PROPOSED METHOD
The main goal of this paper is to distinguish the identical twins by face recognition. For this
purpose, AdaBoost [18] technique is used for face localization step and subimage creation. In the
next step, the subimage will be divided into regions. After that the ZM technique is employed in
each region to extract the feature vector from the region in the subimage of test image. After that
the feature vectors inside the subimages of all images in dataset are obtained using ZM approach.
Finally, comparison between the feature vector of test image and the feature vectors of all images
of dataset is done to select the closest image from dataset as the pair of test image. In the next
Section, the AdaBoost face detection, ZM and its task of feature vector creation are described.
3.1. Face Detection Method
As the mentioned before, face detection step is the second step of this algorithm to recognize
identical twins. This step is based on the combing of successively more complex classifiers in a
3. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
3
cascade structure using AdaBoost [18]. Furthermore, the AdaBoost technique is used to select a
small number of Haar-like features [18].
After finding an object in an image as a face candidate, an ellipse is drowning around the main
location of face in an image[8]. For this purpose, an ellipse model is constructed using five
parameters: X0 and Y0 are the centers of the ellipse, θ is the orientation, αand β are the minor and
the major axes of the ellipse, respectively. Before the calculation of theseparameters, geometric
moments are required to describe. The geometric moments of orderp+q of a digitalimageare
defined as
= ∑ ∑ ( , ) (1)
where p, q = 0, 1, 2, … and f(x, y) is the grey-scale value of the digital image at x and ylocation.
The translation invariant central moments are obtained by placing origin at thecenter of the
image:
= ∑ ∑ ( , )( − ) ( − ) (2)
where = and = yare the centers of the connected components. Thus, centerof gravity
of the connected components is used as the center of the ellipse. The orientationof the ellipse is
computed by determining the least moment of inertia [8].
= arctan( ) (3)
where shows the central moment of the connected components as described in (2). The length
of the major and the minor axes of the best-fit ellipse can also be computed byevaluating the
moment of inertia. With the least and the greatest moments of inertia of anellipse defined as
= ∑ ∑ [( − ) cos − ( − ) sin ] (4)
= ∑ ∑ [( − ) sin − ( − ) cos ] (5)
Length of the major and the minor axes are calculated from [8] as
=
/
(6)
=
/
(7)
To determine how well the best-fit ellipse approximates the connected components, a distance
measure between the connected components and the best-fit ellipse is calculated as follows [8]
∅ = (8)
∅ = (9)
4. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
4
where the Pinside is the number of background points inside the ellipse, Poutside is the number of
points of the connected components that are outside the ellipse, and is the sizeof the
connected components. After drawing of ellipse, a subimage is made according to theellipse and
finally, the ZM is used to extract features inside the subimage.
3.2. Zernike Moment (ZM)
ZM is geometric-based moment that is a two dimensional function of orthogonal polynomials on
the unit disk. The orthogonal moments of ZM are rotation and scale invariants which are suitable
for pattern recognition applications [5][6][8][17]. ZM contains several orthogonal sets of
complex-valued polynomials defined as
( , ) = ( , ) exp tan (10)
where + ≤ 1,n ≥ 0, |m|≤ n, and the radial polynomials { } are defined as
( , ) = ∑ ,| |, ( + )
( | |)/
(11)
where
,| |, = (−1)
( )!
!
| |
!
| |
!
(12)
The ZM of order n and repetition m can be computed as
= ∑ ∑ ( , ) ∗
( , ) (13)
It should be noted that the PZM is computed for positive m because ( , ) = ∗
( , ). Center
of the unit disk is located on the origin of coordinates and so ZM technique is independent of
scaling and rotation.In the next Section, ZM approach will be utilized to extract feature vector
elements.
3.3 Creating feature vector
After face localization and subimage creation, the ZM is computed for each subimage as face
features. The feature vector elements are defined according to ZM orders as
= { | = , + 1, … , } (14)
where j is interval [1,N−1] and so, contains all the ZM from order j to N. Samples of feature
vector elements will be demonstrated in Table 1 for j = 3, 5 and 9, and N = 10. As Table1 shows,
increasing of j decreases the number of elements in each feature vector ( ).
4. EXPERIMENTAL RESULTS
The proposed method is evaluated on two datasets: Twins Days Festival [2] and Iranian Twin
Society [1] which contain 520 and 600 pairs of identical twins images, respectively. The used
datasets contain the scaled and rotated faces with different illuminations. Figure 1 shows the
subimages of some twin test images. The results of identical twins recognition using ZM is
5. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
5
compared with the results of LM [13]. Experiments have been carried out in three steps according
to order of moment. In the first step, order n is in interval [1,6], in the second step, order n is in
interval [6,8] and for third step, order n is in interval [9,10] (Table 2).
In this paper, N is set 10 (N=10) and j varies from 1 to 9. The misclassification rate of all
geometric moments (LM and ZM) is presented in Table 3. The misclassification rate reported in
the table are computed as
=
.
.
(15)
Table 3 shows misclassification rates of LM and ZM. Comparison between geometric moments
in Table 3 proves that higher order moments of the ZM have most information for face
recognition while low-order moments have no significant effect on the system error. According to
the table, LM achieves high misclassification rate on recognition of twins because the rotation of
face in an image has bad effect on the performance of LM. As Table 3 shows, the
misclassification rate of ZM is lower than the LM because ZM is rotation and scale invariant.
Table 1. Feature vector elements based on the ZM
j value jFV feature elements ( kmZM ) Number of
feature elementK M
4
4 0,2,4
30
5 1,3,5
6 0,2,4,6
7 1,3,5,7
8 0,2,4,6,8
9 1,3,5,7,9
10 0,2,4,6,8,10
6
6 0,2,4,6
24
7 1,3,5,7
8 0,2,4,6,8
9 1,3,5,7,9
10 0,2,4,6,8,10
9
9 1,3,5,7,9
11
10 0,2,4,6,8,10
6. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
6
Table 2. Feature vector elements produced by geometric moments in each experiment.
Cat. LM feature elements ZM feature elements
1
n=1, m=1
n=2, m=0,2
n=3, m=1,3
n=4, m=0,2,4
n=5, m=1,3,5
n=6, m=0,2,4,6
n=1, m=1
n=2, m=0,2
n=3, m=1,3
n=4, m=0,2,4
n=5, m=1,3,5
n=6, m=0,2,4,6
2
n=6, m=0,2,4,6
n=7, m=1,3,5,7
n=8, m=0,2,4,6,8
n=6, m=0,2,4,6
n=7, m=1,3,5,7
n=8, m=0,2,4,6,8
3
n=9, m=1,3,5,7,9
n=10, m=0,2,4,6,8,10
n=9, m=1,3,5,7,9
n=10, m=,0,2,4,6,8,10
Visual results of ZM on pair of identical twins are illustrated in Figure 2which refers to Twins
Days Festival [2] and Iranian Twin Society [1] datasets, respectively.
According to numerical and visual results, ZM is able to create informative feature vector inside
the subimages of pair of identical twins which is necessary for recognition of identical twins. The
results prove that ZM is scale and rotation invariant.
Figure 1. Creating of subimage based on the ellipse formation.
Table 4 shows the second phase of testing where the two geometric moments are compared on
finding a pair of a person as the twin ink-nearest persons. In the other words for a test image, his
(her) pair is found in k-nearest persons. In Table 4, the above comparison is done in several ranks
(k), k=3, 5, 7 and 9. Also, visual results of ZM on the second phase of testing are demonstrated in
Figure 3.The results reported in Table 4 are the percentage of identical twins that the pair ofa
person cannot be found in k-nearest persons (16). According to the results of ZM in Table 4and
Figure 3, pair of input image as the identical twin is detected in 3-nearest persons with the
Table 3. Error rate of each geometric moment in different categories. The bold values means the best
values
Cat.
LM ZM
No. of
Feature
Elements
No. of
Misclassificati
on
Error rate
No. of
Feature
Elements
No. of
Misclassificati
on
Error
rate
n=1,2,…,
6
15 20 10% 15 17 8.5%
n=6,7,8 13 18 9.1% 13 13 6.5%
n=9,10 11 12 6.1% 11 8 4%
7. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
7
probability of 95.1% (100%-4.9%) while with LM, the obtained value is with the probability of
91.3% (100%-8.7%). For the other ranks, the ZM approach takes the best error rates. As a result
of Table 4, the detected person as the identical twin using the proposed feature extractor is in k-
nearest persons with high probability.
=
.
.
(16)
5. CONCLUSIONS
This paper is focused on the improving of face recognition systems for distinguishing of a pair of
identical twins. The proposed method is based on the Zernike Moment (ZM) as a feature extractor
to recognize a pair of (identical or non-identical) twins. Also, the location of the face in an image
is detected using the AdaBoost method and then the ZM method is utilized to construct feature
vector elements. Experimental results on two datasets show that the proposed method is superior
to the other geometric moment such as Legendre Moment (LM) and also is robust to rotation and
scaling and changing illumination.
Figure 2. Samples of testing identical twins which were correctly classified by ZM. The first row refers to
the results of ZM on the Twins Days Festival dataset [2] and the second row is the results of ZM on the
Iranian Twin Society dataset [1].
8. Informatics Engineering, an International Journal (IEIJ) ,Vol.2, No.1, March 2014
8
Figure 3. Visual results of ZM on the second phase of testing with rank=3.
Table 4. Results of geometric moments on the second phase of testing with rank=3. Bold values
refer to the best scores.
Rank
Feature extractor
LM ZM
3 8.7% 4.9%
5 5.3% 1.2%
7 3.2% 0%
9 0.9% 0%
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