TY - GEN
T1 - An image segmentation algorithm in image processing based on threshold segmentation
AU - Zhu, Sniping
AU - Xia, Xi
AU - Zhang, Qingrong
AU - Belloulata, Kamel
PY - 2007
Y1 - 2007
N2 - Image segmentation is a key technology in image processing, and threshold segmentation is one of the methods used frequently. Aimed at that only one threshold or several thresholds are set in traditional threshold-based segmentation algorithm, it is difficult to extract the complex information in an image, a new segmentation algorithm that each pixel in the image has its own threshold is proposed. In this algorithm, the threshold of a pixel in an image is estimated by calculating the mean of the grayscale values of its neighbor pixels, and the square variance of the grayscale values of the neighbor pixels are also calculated as an additional judge condition, so that the result of the proposed algorithm is the edge of the image. In fact the proposed algorithm is equal to an edge detector in image processing. Experimental results demonstrate that the proposed algorithm could produce precise image edge, while it is reasonable to estimate the threshold of a pixel through the statistical information of its neighbor pixels.
AB - Image segmentation is a key technology in image processing, and threshold segmentation is one of the methods used frequently. Aimed at that only one threshold or several thresholds are set in traditional threshold-based segmentation algorithm, it is difficult to extract the complex information in an image, a new segmentation algorithm that each pixel in the image has its own threshold is proposed. In this algorithm, the threshold of a pixel in an image is estimated by calculating the mean of the grayscale values of its neighbor pixels, and the square variance of the grayscale values of the neighbor pixels are also calculated as an additional judge condition, so that the result of the proposed algorithm is the edge of the image. In fact the proposed algorithm is equal to an edge detector in image processing. Experimental results demonstrate that the proposed algorithm could produce precise image edge, while it is reasonable to estimate the threshold of a pixel through the statistical information of its neighbor pixels.
UR - https://www.scopus.com/pages/publications/57849136923
U2 - 10.1109/SITIS.2007.116
DO - 10.1109/SITIS.2007.116
M3 - 会议稿件
AN - SCOPUS:57849136923
SN - 9780769531229
T3 - Proceedings - International Conference on Signal Image Technologies and Internet Based Systems, SITIS 2007
SP - 673
EP - 678
BT - Proceedings - International Conference on Signal Image Technologies and Internet Based Systems, SITIS 2007
T2 - 3rd IEEE International Conference on Signal Image Technologies and Internet Based Systems, SITIS'07
Y2 - 16 December 2007 through 18 December 2007
ER -