Master of Science (MS)
Electrical and Computer Engineering
In this thesis, a novel analysis framework is presented in order to automate testing response of an image-feature descriptor algorithm for face recognition under different illumination conditions and white balance calibration over intra- and inter-color space. The experimental results on the OPFD database show that our analysis framework finds the least sensitive channel of a color space for recognizing a face under unknown illumination, unknown white balance, and the both unknown illumination and white balance conditions. The results also show the combination of channels in a color space which are best suited face recognition.
Document Availability at the Time of Submission
Secure the entire work for patent and/or proprietary purposes for a period of one year. Student has submitted appropriate documentation which states: During this period the copyright owner also agrees not to exercise her/his ownership rights, including public use in works, without prior authorization from LSU. At the end of the one year period, either we or LSU may request an automatic extension for one additional year. At the end of the one year secure period (or its extension, if such is requested), the work will be released for access worldwide.
Mohan, Jayesh, "Exploring Invariant Hybrid Color Image Features for Face Recognition Under Illumination Variation" (2014). LSU Master's Theses. 628.