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Face detection

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dc.contributor.advisor Chowdhury, Tarik Ahmed
dc.contributor.author Abdal, Sahar Noor
dc.contributor.author Chowdhury, Mashook Mujib
dc.date.accessioned 2010-10-14T06:30:55Z
dc.date.available 2010-10-14T06:30:55Z
dc.date.copyright 2008
dc.date.issued 2008-01
dc.identifier.other ID 05310049
dc.identifier.other ID 05310052
dc.identifier.uri http://hdl.handle.net/10361/507
dc.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. en_US
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (page 100).
dc.description.abstract 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. en_US
dc.description.statementofresponsibility Sahar Noor Abdal
dc.description.statementofresponsibility Mashook Mujib Chowdhury
dc.format.extent 121 pages
dc.publisher BRAC University en_US
dc.rights 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.
dc.subject Computer science and engineering
dc.title Face detection en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University
dc.description.degree B. Computer Science and Engineering


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