Cemil T.2023-03-012023-03-012014FACE RECOGNITION UNDER POOR ILLUMINATION USING HISTOGRAM EQUALIZATION AND ADAPTIVE SINGLE SCALE RETINEX / Cemil Turan / Suleyman Demirel Universityhttps://repository.sdu.edu.kz/handle/123456789/121The Principal Component Analisys(PCA) is one of the most succesful techniques that have been used in face recognition in the images are sufficiently regular. But this algorithm has some deficiency in some cases such that pose variation, different facial expression or poor illumination. In this paper three different methods were compared and used to increase the recognition rates of them under varying illumination. After using PCA, the other methods (Histogram Equalization and Single scale retinex) were applied to images to have equally distributed illumination for all images. Eventually very high recognition rates were obtained after applying the methods by combining them.Face recognitionthe principal component methodalignment of the instogramsingle-scale retinexArticle