Abstract

Image segmentation is the process of dividing the given image into regions homogeneous with respect to certain features, and which hopefully correspond to real objects in the actual scene. Region-growing algorithms have been used mostly in the analysis of greyscale images; however, some significant work has been completed in the colour. The original image is divided into image blocks, which are not overlapped; then, the mean and variance of each image block were calculated, and the image blocks were divided into homogeneous colour blocks and texture blocks by the variance of it. The initial seed regions are automatically selected depending on calculating the homogeneous colour. The quadtree decomposition algorithm was applied to split and merge the texture blocks. This process is followed until no more pixels can be added. The experimental segmentation results hold favourable consistency in terms of human perception, and confirm effectiveness of the algorithm.

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