Abstract
This paper presents the results of an in-depth analysis of the impact of aggregation of different parts of the face to its recognition process. A novel approach is based on the aggregation of distances determined between histograms, which describe different parts of the face as well as various color channels. In addition, we propose to include thresholding to local descriptors and demonstrate that this type of image processing highly improves the accuracy of classification process. This paper also describes a new approach to converting color images to grayscale images using the variation of each channel in the neighborhood of a given pixel.