Face recognition systems are adversely affected by multiple external factors like illumination, pose, quality of image etc. Illumination is one of the main factors that hinders the performance of the system, the proposed methodology minimizes the effects of varied lighting conditions on the images. The algorithm uses Histogram of Oriented Gradients (HOG) technique for feature extraction and Error correcting output Codes (ECOC) Multi class Support Vector Machines (SVM) for classification. The results are verified using ORL and Extended Yale Face Database B image sets and good accuracy was obtained in the classification of poor and well illuminated images.
|Number of pages||4|
|Journal||International Journal of Scientific and Technology Research|
|Publication status||Published - 04-2020|
All Science Journal Classification (ASJC) codes
- Management of Technology and Innovation