登入選單

返回Google圖書搜尋

An Improved Multithreshold Segmentation Algorithm Based on Graph Cuts Applicable for Irregular Image

Yanzhu Hu Jiao WangXinbo AiXu Zhuang

出版	Infinite Study
主題	Mathematics / Applied
URL	http://books.google.com.hk/books?id=6ATUDwAAQBAJ&hl=&source=gbs_api
EBook	SAMPLE

註釋

In order to realize themultithreshold segmentation of images, an improved segmentation algorithm based on graph cut theory using artificial bee colony is proposed. A newweight function based on gray level and the location of pixels is constructed in this paper to calculate the probability that each pixel belongs to the same region. On this basis, a new cost function is reconstructed that can use both square and nonsquare images.Then the optimal threshold of the image is obtained through searching for theminimum value of the cost function using artificial bee colony algorithm. In this paper, public dataset for segmentation and widely used images were measured separately. Experimental results show that the algorithm proposed in this paper can achieve larger Information Entropy (IE), higher Peak Signal to Noise Ratio (PSNR), higher Structural Similarity Index (SSIM), smaller Root Mean Squared Error (RMSE), and shorter time than other image segmentation algorithms.