Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398158
P. Prathik, R. Nafde, K. Manikantan, S. Ramachandran
Feature Extraction plays a very important role in Face Recognition technology. This paper proposes a novel Discrete Cosine Transform (DCT) fusion technique based on facial symmetry. Also proposed are DCT subset matrix selection based on aspect ratio of the image and pre-processing concepts, namely Local Histogram Equalization to remove illumination variation and Scale normalization using skin detection for colored images. The performance of proposed techniques is evaluated by computing the recognition rate and number of features selected for ORL, Extended Yale B and Color FERET databases.
{"title":"Feature Extraction using DCT fusion based on facial symmetry for enhanced face recognition","authors":"P. Prathik, R. Nafde, K. Manikantan, S. Ramachandran","doi":"10.1109/ICCICT.2012.6398158","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398158","url":null,"abstract":"Feature Extraction plays a very important role in Face Recognition technology. This paper proposes a novel Discrete Cosine Transform (DCT) fusion technique based on facial symmetry. Also proposed are DCT subset matrix selection based on aspect ratio of the image and pre-processing concepts, namely Local Histogram Equalization to remove illumination variation and Scale normalization using skin detection for colored images. The performance of proposed techniques is evaluated by computing the recognition rate and number of features selected for ORL, Extended Yale B and Color FERET databases.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121080791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398207
H. B. Kekre, T. Sarode, R. Vig
Extraction of region of interest (ROI) from a palmprint considerably improves the efficiency of identification systems as ROI extracted palmprint images have more entropy and require less processing and storage. In this paper we have extracted the ROI of palmprints of two sets of databases, Hongkong Polytechnic University low resolution palmprint Database and high resolution indigenous database. The method used here employs image processing techniques including dynamic thresholding for binarization, centroid determination, boundary extraction using morphological operations, Euclidean distance calculations from the centroid, valley points determination after smoothening the Euclidean distance plot, from which finally the ROI is extracted.For the above mentioned datasets, the ROI of size 128 × 128 and 256 × 256 respectively have been extracted using this technique.
从掌纹中提取感兴趣区域（ROI）可大大提高识别系统的效率，因为提取 ROI 的掌纹图像熵值更大，所需的处理和存储也更少。在本文中，我们提取了香港理工大学低分辨率掌纹数据库和高分辨率本地数据库两组数据库中掌纹的 ROI。本文采用的方法运用了图像处理技术，包括动态阈值二值化、确定中心点、使用形态学运算提取边界、计算中心点的欧氏距离、平滑欧氏距离图后确定谷点，最后从中提取 ROI。
{"title":"An effectual method for extraction of ROI of palmprints","authors":"H. B. Kekre, T. Sarode, R. Vig","doi":"10.1109/ICCICT.2012.6398207","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398207","url":null,"abstract":"Extraction of region of interest (ROI) from a palmprint considerably improves the efficiency of identification systems as ROI extracted palmprint images have more entropy and require less processing and storage. In this paper we have extracted the ROI of palmprints of two sets of databases, Hongkong Polytechnic University low resolution palmprint Database and high resolution indigenous database. The method used here employs image processing techniques including dynamic thresholding for binarization, centroid determination, boundary extraction using morphological operations, Euclidean distance calculations from the centroid, valley points determination after smoothening the Euclidean distance plot, from which finally the ROI is extracted.For the above mentioned datasets, the ROI of size 128 × 128 and 256 × 256 respectively have been extracted using this technique.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125897711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398135
P. C. Ravoor, S. R. Rupanagudi, B. Ranjani
Touch-screens have emerged as a very popular technology. Touch-screens pervade all electronic devices from laptops to mobile-phones to advanced security systems, up to such a point that any device that does not use touch-screens is deemed outdated. Touch-screens can be broadly classified into three types - capacitive, resistive and imaging. The major advantage of imaging touch screens is its low cost as compared to its counterparts and their upgradation also involves minimal changes to hardware. In areas where there is no necessity of slim touch-screens, image processing touch screens are of a great asset. Essentially, imaging touch-screens are capable of the same functionalities, if not more, as their slimmer counterparts. This includes the latest trend in touch-screen technology, “multi-touch”. This paper discusses a novel algorithm to detect multiple points of contact on an imaging touch surface. The algorithm was implemented using Java programming language and a high level of accuracy was achieved in detecting multiple finger tip blobs for various experiments conducted.
{"title":"Detection of multiple points of contact on an imaging touch-screen","authors":"P. C. Ravoor, S. R. Rupanagudi, B. Ranjani","doi":"10.1109/ICCICT.2012.6398135","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398135","url":null,"abstract":"Touch-screens have emerged as a very popular technology. Touch-screens pervade all electronic devices from laptops to mobile-phones to advanced security systems, up to such a point that any device that does not use touch-screens is deemed outdated. Touch-screens can be broadly classified into three types - capacitive, resistive and imaging. The major advantage of imaging touch screens is its low cost as compared to its counterparts and their upgradation also involves minimal changes to hardware. In areas where there is no necessity of slim touch-screens, image processing touch screens are of a great asset. Essentially, imaging touch-screens are capable of the same functionalities, if not more, as their slimmer counterparts. This includes the latest trend in touch-screen technology, “multi-touch”. This paper discusses a novel algorithm to detect multiple points of contact on an imaging touch surface. The algorithm was implemented using Java programming language and a high level of accuracy was achieved in detecting multiple finger tip blobs for various experiments conducted.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130896330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398193
V. Bora, A. G. Kothari, A. Keskar
The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, a new algorithm to detect suspicious lesions in mammograms is developed using tolerance near set approach. Near set theory provides a method to establish resemblance between objects contained in a disjoint set. Objects that have, in some degree, affinities are considered perceptually near each other. The probe functions are defined in terms of digital images such as: gray level, entropy, color, texture, etc. Objects in visual field are always presented with respect to the selected probe functions. Moreover, it is the probe functions that are used to measure characteristics of visual objects and similarities among perceptual objects, making it possible to determine if two objects are associated with the same pattern. The algorithm has been verified on mammograms from the CICRI (Central India Cancer Research Institute, Nagpur, India) and Mias database. Results of segmentation are compared with Otsu method of segmentation.. Once the features are computed for each region of interest (ROI), they are used as inputs to a supervised Back Propagation Neural Network. Results indicate that Tolerance Near sets segmentation method performs better than otsu method in terms of classification accuracy.
{"title":"Tumor segmentation by tolerance near set approach in mammography and lesion classification with neural network","authors":"V. Bora, A. G. Kothari, A. Keskar","doi":"10.1109/ICCICT.2012.6398193","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398193","url":null,"abstract":"The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, a new algorithm to detect suspicious lesions in mammograms is developed using tolerance near set approach. Near set theory provides a method to establish resemblance between objects contained in a disjoint set. Objects that have, in some degree, affinities are considered perceptually near each other. The probe functions are defined in terms of digital images such as: gray level, entropy, color, texture, etc. Objects in visual field are always presented with respect to the selected probe functions. Moreover, it is the probe functions that are used to measure characteristics of visual objects and similarities among perceptual objects, making it possible to determine if two objects are associated with the same pattern. The algorithm has been verified on mammograms from the CICRI (Central India Cancer Research Institute, Nagpur, India) and Mias database. Results of segmentation are compared with Otsu method of segmentation.. Once the features are computed for each region of interest (ROI), they are used as inputs to a supervised Back Propagation Neural Network. Results indicate that Tolerance Near sets segmentation method performs better than otsu method in terms of classification accuracy.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121934759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398167
S. Kadge, G. Bhatia
The Social networking site play an important role in today's world thereby attracting lots of researchers to take advantage of the user's information available in these sites. Mining the database using different algorithms like association rule mining require multiple database scan. In this research forecasting is based on the directed weighted social graph. It deals with visualization of a dataset and prediction of some occurrences based upon this data. The methodology proposed is to generate a social graph of user's actions and predict the future social activities using graph mining. A dataset from the social networking site is considered and converted to a directed, weighted social graph. This graph is updated dynamically based on the changes in the database of social networking site. By creating some mathematical rules applied on the graph, we could project the future activities of users in terms of community memberships, the strength of a relationship between two users without knowing the content of the discussion. We can also find the most popular community. To find the efficiency of this method, the result interpreted by this experiment will be compared to other methods used for prediction like Apriori etc.
{"title":"Graph based forecasting for Social networking site","authors":"S. Kadge, G. Bhatia","doi":"10.1109/ICCICT.2012.6398167","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398167","url":null,"abstract":"The Social networking site play an important role in today's world thereby attracting lots of researchers to take advantage of the user's information available in these sites. Mining the database using different algorithms like association rule mining require multiple database scan. In this research forecasting is based on the directed weighted social graph. It deals with visualization of a dataset and prediction of some occurrences based upon this data. The methodology proposed is to generate a social graph of user's actions and predict the future social activities using graph mining. A dataset from the social networking site is considered and converted to a directed, weighted social graph. This graph is updated dynamically based on the changes in the database of social networking site. By creating some mathematical rules applied on the graph, we could project the future activities of users in terms of community memberships, the strength of a relationship between two users without knowing the content of the discussion. We can also find the most popular community. To find the efficiency of this method, the result interpreted by this experiment will be compared to other methods used for prediction like Apriori etc.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122560082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398150
S. Upadhya
The beauty of human speech lies in the complexity of the different sounds that can be produced by a few tubes and muscles. This intricacy, however, makes speech processing a challenging task. One defining characteristic of speech is its pitch. Detecting this Pitch or equivalently, fundamental frequency detection of a speech signal is important in many speech applications. Pitch detectors are used in vocoders, speaker identification and verification systems and also as aids to the handicapped. Because of its importance many solutions to detect pitch has been proposed both in time and frequency domains. One such solution is pitch detection is by using Autocorrelation method and Average Magnitude Difference Function (AMDF), method which are analyses done in the time domain and the other is detecting the harmonic nature in the frequency domain. This paper gives the implementation results of the pitch period estimated in the time and frequency domains for vowel and fricative speech sounds, both for male and female speakers.
{"title":"Pitch detection in time and frequency domain","authors":"S. Upadhya","doi":"10.1109/ICCICT.2012.6398150","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398150","url":null,"abstract":"The beauty of human speech lies in the complexity of the different sounds that can be produced by a few tubes and muscles. This intricacy, however, makes speech processing a challenging task. One defining characteristic of speech is its pitch. Detecting this Pitch or equivalently, fundamental frequency detection of a speech signal is important in many speech applications. Pitch detectors are used in vocoders, speaker identification and verification systems and also as aids to the handicapped. Because of its importance many solutions to detect pitch has been proposed both in time and frequency domains. One such solution is pitch detection is by using Autocorrelation method and Average Magnitude Difference Function (AMDF), method which are analyses done in the time domain and the other is detecting the harmonic nature in the frequency domain. This paper gives the implementation results of the pitch period estimated in the time and frequency domains for vowel and fricative speech sounds, both for male and female speakers.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126556651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398092
Lalitha Kumari, Subaashini
In this paper, a novel technique is proposed for energy efficient switching transmission scheme in a wireless sensor network (WSN). Distributed sensors can cooperate with the neighborhood and transmit their data to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and distance among the sensors. The analytic performances of two MIMO transmission modes and SIMO can be accessed by investigating the statistical properties of a correlated virtual multiple-input multiple-output (MIMO) channel between the sensors and data collector. The energy efficiencies of two MIMO transmission modes namely spatial multiplexing, transmit diversity are also evaluated. Based on these result, a new energy efficient mode switching criterion between spatial multiplexing, transmit diversity and SIMO suitable to a WSN is derived.
{"title":"Energy-efficient switching transmission scheme for a cooperative WSN","authors":"Lalitha Kumari, Subaashini","doi":"10.1109/ICCICT.2012.6398092","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398092","url":null,"abstract":"In this paper, a novel technique is proposed for energy efficient switching transmission scheme in a wireless sensor network (WSN). Distributed sensors can cooperate with the neighborhood and transmit their data to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and distance among the sensors. The analytic performances of two MIMO transmission modes and SIMO can be accessed by investigating the statistical properties of a correlated virtual multiple-input multiple-output (MIMO) channel between the sensors and data collector. The energy efficiencies of two MIMO transmission modes namely spatial multiplexing, transmit diversity are also evaluated. Based on these result, a new energy efficient mode switching criterion between spatial multiplexing, transmit diversity and SIMO suitable to a WSN is derived.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127224255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398191
S. Mishra, U. Agrawal, G. Nandi
It has been seen that Social network analysis is gaining its applicability in several areas like business, marketing, biology, disease modeling, and anti-terrorism. In this paper, we have discussed its practical application in the domain of computer network to identify distribution of computer viruses flowing through the network. To the best of our knowledge this is a novel idea and is based on the gSpan (Graph based substructure Pattern Mining) algorithm for identifying frequent pattern of viruses flowing in a particular region of connected nodes. This crusades make analysist enabled to deal with the problems and deploy more efficient antivirus in that region of nodes.
{"title":"CVPD: A tool based on a social network analysis to combating viruses propagation","authors":"S. Mishra, U. Agrawal, G. Nandi","doi":"10.1109/ICCICT.2012.6398191","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398191","url":null,"abstract":"It has been seen that Social network analysis is gaining its applicability in several areas like business, marketing, biology, disease modeling, and anti-terrorism. In this paper, we have discussed its practical application in the domain of computer network to identify distribution of computer viruses flowing through the network. To the best of our knowledge this is a novel idea and is based on the gSpan (Graph based substructure Pattern Mining) algorithm for identifying frequent pattern of viruses flowing in a particular region of connected nodes. This crusades make analysist enabled to deal with the problems and deploy more efficient antivirus in that region of nodes.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127397615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398133
G. Prakash, M. Kulkarni, U. Sripati, M. N. Kalyanpur
Free Space Optical (FSO) communication is an emerging transmission technique to transmit high data rates without using cables. This technology is expected to revolutionize the present communication system architectures both in the terrestrial and the in -space architecture. Atmospheric effects can significantly degrade the performance of FSO systems. This reduces the SNR and leads to impaired performance. FSO channels can be modeled using Gamma-Gamma, Weibull, Log-Normal, K distribution functions. Error control codes can help to mitigate atmospheric turbulence induced signal fading in free space optical communication links. Luby Transform codes belong to a class of error control codes called Fountain codes and are meant for erasure channels. In this paper, we propose encoding FSO links with Luby Transform (LT) codes for error channels. Decoding is done using belief propagation with Log Likelihood Ratio and results are obtained for different modulation schemes under different channel distributions.
{"title":"Performance analysis of Free Space Optical links encoded using Luby Transform codes","authors":"G. Prakash, M. Kulkarni, U. Sripati, M. N. Kalyanpur","doi":"10.1109/ICCICT.2012.6398133","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398133","url":null,"abstract":"Free Space Optical (FSO) communication is an emerging transmission technique to transmit high data rates without using cables. This technology is expected to revolutionize the present communication system architectures both in the terrestrial and the in -space architecture. Atmospheric effects can significantly degrade the performance of FSO systems. This reduces the SNR and leads to impaired performance. FSO channels can be modeled using Gamma-Gamma, Weibull, Log-Normal, K distribution functions. Error control codes can help to mitigate atmospheric turbulence induced signal fading in free space optical communication links. Luby Transform codes belong to a class of error control codes called Fountain codes and are meant for erasure channels. In this paper, we propose encoding FSO links with Luby Transform (LT) codes for error channels. Decoding is done using belief propagation with Log Likelihood Ratio and results are obtained for different modulation schemes under different channel distributions.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"XL 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131199421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-31DOI: 10.1109/ICCICT.2012.6398140
K. Karande
In this paper we have proposed wavelet based edge detection algorithm that combines the coefficients of wavelet transforms on a series of scales. The outcome of this algorithm is edginess like information further used to obtain Independent Components using ICA algorithms. The combination of Multiscale wavelet based edge detection and Independent Component Analysis (ICA) is used for Face Recognition becomes a novel approach. The independent components obtained by ICA algorithms are used as feature vectors for classification. The Euclidean distance (L2) classifier is used for testing of images. The algorithm is tested on two different databases i.e Asian face database and Indian face database of face images for variation in illumination, facial expressions and facial poses up to 1800rotation angle. Encouraging results of this unique approach of face recognition has given future direction for research work in this area.
{"title":"Multiscale wavelet based edge detection and Independent Component Analysis (ICA) for Face Recognition","authors":"K. Karande","doi":"10.1109/ICCICT.2012.6398140","DOIUrl":"https://doi.org/10.1109/ICCICT.2012.6398140","url":null,"abstract":"In this paper we have proposed wavelet based edge detection algorithm that combines the coefficients of wavelet transforms on a series of scales. The outcome of this algorithm is edginess like information further used to obtain Independent Components using ICA algorithms. The combination of Multiscale wavelet based edge detection and Independent Component Analysis (ICA) is used for Face Recognition becomes a novel approach. The independent components obtained by ICA algorithms are used as feature vectors for classification. The Euclidean distance (L2) classifier is used for testing of images. The algorithm is tested on two different databases i.e Asian face database and Indian face database of face images for variation in illumination, facial expressions and facial poses up to 1800rotation angle. Encouraging results of this unique approach of face recognition has given future direction for research work in this area.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131903645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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