In this paper, we introduce the human visual system-based several new (a) methods to visualize the very small differences in intensities without big changes of primary image information and (b) measures that quality the visuality of both grayscale and color images. Several illustrative examples are also presented. The proposed concepts can be used for many image processing, computer vision and recognition system applications.
This paper proposes a new color image representation and multiple feature fusion based method for improving color face recognition performance under different lighting conditions. First, a new image color image representation has been derived. Second, a quaternion gradient has been given to enhance and extract the faces/object's edges, contours, and texture. Also, we propose a novel feature representation based on Quaternion Gradient-based LBP tool for color face recognition. Finally, we present a concept of combining the color facial recognition system, which is based on the local quaternion gradients based binary patterns LBP Image Representation, and a new color-to-gray new mapping. The presented concept can be used for surveillance, security systems, computer animation, face tagging, human–computer interface, biometric identification, behavioral analysis, content-based image and video indexing applications.