An Image Segmentation Algorithm in Image Processing Based on Threshold Segmentation

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.

[1]  K. Bilger,et al.  Threshold calculation for segmented attenuation correction in PET with histogram fitting , 1999, 1999 IEEE Nuclear Science Symposium. Conference Record. 1999 Nuclear Science Symposium and Medical Imaging Conference (Cat. No.99CH37019).

[2]  Paul Wintz,et al.  Digital image processing (2nd ed.) , 1987 .

[3]  K. Fazekas,et al.  Threshold procedures and image segmentation , 2005, 47th International Symposium ELMAR, 2005..

[4]  Ling-Hwei Chen,et al.  New method for multilevel thresholding using the symmetry and duality of the histogram , 1993, J. Electronic Imaging.

[5]  Peng-Yeng Yin,et al.  A new method for multilevel thresholding using symmetry and duality of the histogram , 1994, Proceedings of ICSIPNN '94. International Conference on Speech, Image Processing and Neural Networks.

[6]  P.K Sahoo,et al.  A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..

[7]  Weinan Chen,et al.  Fast recursive algorithms for two-dimensional thresholding , 1998, Pattern Recognit..

[8]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  W. Müller-Schauenburg,et al.  Threshold calculation for segmented attenuation correction in PET with histogram fitting , 1999 .

[10]  Wang Hai.  A Fast Algorithm for Two-dimensional Otsu Adaptive Threshold Algorithm , 2007 .

[11]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[12]  Jack Koplowitz,et al.  On the Edge Location Error for Local Maximum and Zero-Crossing Edge Detectors , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Ge Yu,et al.  Fast search for thresholds from 1D and 2D histograms by an iterative algorithm for image segmentation , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[14]  Xue Dong Yang,et al.  An improved threshold selection method for image segmentation , 1993, Proceedings of Canadian Conference on Electrical and Computer Engineering.

[15]  Han Si.  A Survey of Thresholding Methods for Image Segmentation , 2002 .