Face detection
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2008.
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BRAC University
2010
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10361-5072022-01-26T10:04:58Z Face detection Abdal, Sahar Noor Chowdhury, Mashook Mujib Chowdhury, Tarik Ahmed Department of Computer Science and Engineering, BRAC University Computer science and engineering This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2008. Cataloged from PDF version of thesis report. Includes bibliographical references (page 100). Human face detection plays an important role in applications like face recognition, video surveillance, human computer interface, face image database management and many more. In modern multimedia systems, video and image signals usually need to be indexed or retrieved according to their contents. In our thesis, we implement a color characteristic for use in detection of frontal human faces in color images with complex backgrounds i.e. a color based technique to detect frontal human face had been developed and implemented. A technique for detecting frontal human faces in color images is described that first separates skin region from non-skin region and then locates faces within skin regions. Using color information in an image is one of the various possible techniques for face detection. The technique involves conversion of a color image into a gray scale image in such a way that the gray values in the pixel shows the likelihood of the pixel belonging to the skin. Obtained gray scale image is then segmented to skin and non-skin regions, and a model face, representing front face is used in template matching process to detect face within skin regions i.e. to find which of the candidates is/are actually a face. Later, the false-positive and false-negative errors of the implemented face detection technique on color images are calculated. The experimental results show that this method can detect faces in v the images from different sources with good efficiency. Since faces are common elements in video and image signals, the proposed face detection technique is an advance towards the goal of content-based video and image indexing and retrieval. Sahar Noor Abdal Mashook Mujib Chowdhury B. Computer Science and Engineering 2010-10-14T06:30:55Z 2010-10-14T06:30:55Z 2008 2008-01 Thesis ID 05310049 ID 05310052 http://hdl.handle.net/10361/507 BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 121 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| topic |
Computer science and engineering |
| spellingShingle |
Computer science and engineering Abdal, Sahar Noor Chowdhury, Mashook Mujib Face detection |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2008. |
| author2 |
Chowdhury, Tarik Ahmed |
| author_facet |
Chowdhury, Tarik Ahmed Abdal, Sahar Noor Chowdhury, Mashook Mujib |
| format |
Thesis |
| author |
Abdal, Sahar Noor Chowdhury, Mashook Mujib |
| author_sort |
Abdal, Sahar Noor |
| title |
Face detection |
| title_short |
Face detection |
| title_full |
Face detection |
| title_fullStr |
Face detection |
| title_full_unstemmed |
Face detection |
| title_sort |
face detection |
| publisher |
BRAC University |
| publishDate |
2010 |
| url |
http://hdl.handle.net/10361/507 |
| work_keys_str_mv |
AT abdalsaharnoor facedetection AT chowdhurymashookmujib facedetection |
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1814307102318919680 |