This study was designed to use Histogram Equalization and SVM based method to build a face recognition system under variant pose and illumination condition. Illumination compensation plays a vital role in face recognition. If the system can detect illumination variant faces, it increases the efficiency of the system. To compare the latest illumination compensation algorithm, Oriented Local Histogram Equalization (OLHE) which has proven to have exceptionally high performance under extreme lighting conditions with the previous state of the art algorithms such as Local Binary Pattern (LBP) and Local gradient Oriented Binary Patterns (LGOBP) as they encode micro-patterns giving the efficient descriptors for face recognition. It proposed that the illumination compensation algorithm OLHE will give the highest efficiency rates among the three algorithms taken into consideration and is the best illumination compensation algorithm available by analyzing their performance on the datasets CMU-PIE and extended YALE B. © 2015 Academic Journals Inc.