Daffodil International University
Faculty of Science and Information Technology => Recent Technologies and Trends in Software Engineering => Software Engineering => Image Processing Computer Networks => Topic started by: iftekhar.swe on September 05, 2018, 03:49:20 PM
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Abstract: Face recognition system is a computer based biometric information processing for automatically identifying or verifying a person from a digital image or a video frame. The significance of this research area is increasing day by day. Although the existing methods of face verification system perform well under certain conditions, there are still challenging problems due to several issues such as pose variation, facial expression variation, occlusion, imaging conditions, illuminations, size variations, age variations, orientations, etc. This paper addresses the problem of recognizing human faces despite the variations of pose and size. To handle these problems, we mainly focus on dynamic block size. Instead of uniform block, we propose Dynamic Size Blocks (DSB) considering most prominent face features such as eye, eyebrow, nose, mouth, chin, cheek, fore-head, etc., based on facial landmarks. In this feature based approach, we use a Dynamic Local Ternary Pattern (DLTP) for extracting facial feature information from each dynamic block. Then we perform a square-root of Chi-Square distance for similarity measurement of each block. We use a Support Vector Machine (SVM) classifier for face verification. We performed a comprehensive experimental evaluation on Labeled Faces in the Wild (LFW) dataset with restricted settings original images. Our proposed method has achieved an accuracy of 74.08% on all test images and 82.26% on dataset images excluding extreme pose variations.
Full-Paper: https://www.researchgate.net/profile/Md_Efat/publication/304083904_Dynamic_Blocks_for_Face_Verification/links/5765d55b08ae421c4489d556/Dynamic-Blocks-for-Face-Verification.pdf
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Interesting work. Please inform me further.
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Thanks for sharing. :)
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Informative post, thank you for sharing this post