Digital Image Processing -3/E.

TL;DR: The intended approach to segment classification deploys a customized MLP topology to classify and characterize the segments, which deals with a supervised learning by error correction – propagation of pattern inputs with changes in synaptic weights in a cyclic processing, with accurate recognition as well as easy parameter adjustment.

TL;DR: This paper attempts to propose an algorithm to analyze and classify the type of motion in a crowd based on texture analysis of video sequence, which is used to classify the motion into predefined classes.

TL;DR: Experimental results show that high contour accuracy can be obtained to detect image by the algorithm, and in regional consistency, the algorithm is better than some traditional algorithms of image edge detection.

TL;DR: The image processing method is used to reduce the light intensity towards a person's face to the approximate level of the indoor illumination, thus reducing the pupil contraction frequency.