The paper presents a fast vehicle plate location method based on HSV space and texture,which makes full use of the characteristic that license plates have relatively steadfast color to quickly and accurately locate areas related to the color.

For reducing noise and preferably keeping the edge of the images,the mean-shift algorithm based on HSV space was proposed.

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.

Shadow detection based on HSV color space characteristic and Gabor screener

The statistical features of color histogram of three independence variables in HSV color space,and independent characteristics of hue,saturation,and brightness are adopted to express the information of color of wood surface in this paper.

Then get the coarse shadow area where the shadow detection based on the HSV color space is only applied in.