Non-rigid object tracking via color segmentation and part model match;

A new license plate location method, which is based on color segmentation,license plate shape analysis and mathematic morphology operation, is presented.

The image processing procedure such as color segmentation, run length encoding (RLE), connected components finding, and region merging are introduced .

One of the problems of Self-Organizing Maps in color segmentation is that the numbers of clusters should be specified in advance and the success of the clustering algorithm largely depends on the specified number of clusters.

Another method is to use color segmentation and multiplayer perceptron classifier.

An approach for automatic recognition of a vehicle license using color segmentation and hierarchical hybird integrated classifier is presented.

A color segmentation based adaptive weight algorithm is adopted to improve the accuracy of distinctiveness estimation, which has an important influence on the result of disparity matching.

Then,based on the features of H and S sub-channels of HSV color space,this paper uses K-means algorithm to classify those areas into nine parts.

The algorithm employs information of the color image in HSV color space to construct a five_scale gray image, pre_processes the image with morphological method, then locates and segments the vehicle license plate by analyzing and discriminating the statistical_letter_frequency property of every possible regions.

This paper introduces HSV color space and an algorithm of automatic recognition character color.

In this paper, through on-line skin-color training technique, the filter based on feature distance in HSV color space erases much color noise due to digital vision systems, and a skin-color statistic model of current terminal user is achieved precisely after color information of training region is analyzed.

On the basis of analysis and comparison of the existing algorithms, a new visualization method of trees using HSV color space based on IBR is presented.