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Proceedings ArticleDOI

A framework for image classification for an efficient dictionary based face recognition system

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TLDR
The proposed red length based image classification algorithm is to perform face recognition based on class specific dictionaries and to train the samples from / to each class to efficient dictionary based facial recognition.
Abstract
The digital multimedia image processing and its functionality of Face recognition have become more flexible. In a variety of digital forensic applications such as source identification, content analysis and authentication, it is necessary to recognize the source with training set. The proposed red length based image classification algorithm is to perform face recognition based on class specific dictionaries and to train the samples from / to each class. The class specific dictionaries are formed with some fixed number of color components. Then compares the test image with the threshold specific class and extract the minimal training set stored in the dictionary. The time taken for the image comparison leads to efficient dictionary based facial recognition which can be then used as proof of evidence towards image forensics.

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Citations
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a / Automatic Attendance and Mobile Learning System in Sensor Enabled Heterogeneous and Dynamic University Environment

TL;DR: A framework for improving class attendance based on GPS and face detection, and a new learning environment where students can use devices like enabled devices, iPad, Tab, iPhone, blackberry, laptop etc. for class quizzes and assignments are defined.
Journal Article

Automatic Attendance and Mobile Learning System in Sensor-Enabled Heterogeneous and Dynamic University Environment.

TL;DR: A framework for improving class attendance based on GPS and face detection, and new learning environment where students can use devices like enabled devices, iPad, Tab, iPhone, blackberry, laptop etc. for class quizzes and assignments is defined.
References
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Journal ArticleDOI

Robust Face Recognition via Sparse Representation

TL;DR: This work considers the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise, and proposes a general classification algorithm for (image-based) object recognition based on a sparse representation computed by C1-minimization.
Journal ArticleDOI

Face recognition: A literature survey

TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Book ChapterDOI

Gabor feature based sparse representation for face recognition with gabor occlusion dictionary

TL;DR: The number of atoms is significantly reduced in the computed Gabor occlusion dictionary, which greatly reduces the computational cost in coding the occluded face images while improving greatly the SRC accuracy.
Journal ArticleDOI

Time Frequency and Wavelets in Biomedical Signal Processing

TL;DR: The Body Explorer is an interactive software program that offers 250 anatomical images in cross-section of the Visible Human Male and can be considered an anatomical atlas, having no text to accompany the images.
Proceedings ArticleDOI

Towards a practical face recognition system: Robust registration and illumination by sparse representation

TL;DR: It is shown that the proposed simple and practical face recognition system can efficiently and effectively recognize faces under a variety of realistic conditions, using only frontal images under the proposed illuminations as training.