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An Image Segmentation Algorithm Converged Edge Color in Measure Natural Scenes

Peng Li, Ling Li, Min Li


Mean shift algorithm in natural scenes has been gained widespread attention in image segmentation. The algorithm and spatial coordinates of the pixel gray values form a joint feature space, through an iterative process to achieve image filtering, and filtering results realizes the image region segmentation by region growing. The traditional segmentation method is based on the single visual cues. The paper had proposed a combination of two kinds of local edge measure natural scene color image segmentation method. Firstly, using logistic regression model 200 color images for training, establish the boundary edges of the object measure regression model. Secondly, it is using this model to predict the boundaries of each pixel in the image confidence. The comparative experiment results of nearly 20 quantitative and visual images show that the proposed method can effectively control the generation of over-segmentation and under-segmentation, and the border region has better positioning effect.


region segmentation, natural scene image, edge detection, mean shift algorithm

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