JOURNAL ARTICLE

Texture Image Segmentation Using Without Re-initialization Geodesic Active Contour Model

Abstract

A novel method of texture image segmentation is proposed, which has three advantages compared to other active contours.First, by combining the gray levels of pixels with texture information of an image, this method can be used for segmentation of a texture image or a non-texture image.Second, the method has low computation complexity because local binary pattern (LBP) is employed to extract texture features.And last, the proposed algorithm can avoid the additional computation problem without reinitialization of signal distance function repeatedly.The segmentation tests show that the proposed segmentation method is efficient, accurate, fast and robust.

Keywords:
Initialization Artificial intelligence Computer vision Computer science Image segmentation Image texture Active contour model Texture (cosmology) Segmentation Geodesic Pattern recognition (psychology) Scale-space segmentation Image (mathematics) Mathematics Geometry

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Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

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