A novel image thresholding method based on Parzen window estimate

Image segmentation is one of the most important and fundamental tasks in image processing and techniques based on image thresholding are typically simple and computationally efficient. However, the image segmentation results depend heavily on the chosen image thresholding methods. In this paper, histogram is integrated with the Parzen window technique to estimate the spatial probability distribution of gray-level image values, and a novel criterion function is designed. By optimizing the criterion function, an optimal global threshold is obtained. The experimental results for synthetic real-world and images demonstrate the success of the proposed image thresholding method, as compared with the OTSU method, the MET method and the entropy-based method.

[1]  Y. J. Zhang,et al.  A survey on evaluation methods for image segmentation , 1996, Pattern Recognit..

[2]  Chein-I Chang,et al.  A relative entropy-based approach to image thresholding , 1994, Pattern Recognit..

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

[4]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

[5]  Jianbin Xie,et al.  A fast two-dimensional entropic thresholding algorithm , 2008, 2008 International Conference on Information and Automation.

[6]  Andrew K. C. Wong,et al.  A new method for gray-level picture thresholding using the entropy of the histogram , 1985, Comput. Vis. Graph. Image Process..

[7]  Lorenzo Bruzzone,et al.  Image thresholding based on the EM algorithm and the generalized Gaussian distribution , 2007, Pattern Recognit..

[8]  Darrel L. Chenoweth,et al.  Two-dimensional entropic segmentation , 1999, Pattern Recognit. Lett..

[9]  Azeddine Beghdadi,et al.  Entropic Thresholding Using a Block Source Model , 1995, CVGIP Graph. Model. Image Process..

[10]  William A. Yasnoff,et al.  Error measures for scene segmentation , 1977, Pattern Recognit..

[11]  Kari Torkkola,et al.  Feature Extraction by Non-Parametric Mutual Information Maximization , 2003, J. Mach. Learn. Res..

[12]  Ladislav Halada,et al.  Histogram concavity analysis by quasicurvature , 1987 .

[13]  Olivier D. Faugeras,et al.  Segmentation of Images Having Unimodal Distributions , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Nabih N. Abdelmalek,et al.  Maximum likelihood thresholding based on population mixture models , 1992, Pattern Recognit..

[15]  Shyang Chang,et al.  A new criterion for automatic multilevel thresholding , 1995, IEEE Trans. Image Process..

[16]  Azriel Rosenfeld,et al.  Fast pyramidal algorithms for image thresholding , 1995, Pattern Recognit..

[17]  David G. Stork,et al.  Pattern Classification (2nd ed.) , 1999 .

[18]  Ronald W. Schafer,et al.  Multilevel thresholding using edge matching , 1988, Comput. Vis. Graph. Image Process..

[19]  R. Kirby,et al.  A Note on the Use of (Gray Level, Local Average Gray Level) Space as an Aid in Threshold Selection. , 1979 .

[20]  Azriel Rosenfeld,et al.  Region Extraction by Averaging and Thresholding , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[21]  José Martínez-Aroza,et al.  A measure of quality for evaluating methods of segmentation and edge detection , 2001, Pattern Recognit..

[22]  Frank Y. Shih,et al.  Image Segmentation , 2007, Encyclopedia of Biometrics.

[23]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[24]  Ahmed S. Abutaleb,et al.  Automatic thresholding of gray-level pictures using two-dimensional entropy , 1989, Comput. Vis. Graph. Image Process..

[25]  Chin-Wen Yang,et al.  A fast two-dimensional entropic thresholding algorithm , 1994, Pattern Recognit..

[26]  Shyi-Chyi Cheng,et al.  A Neural Network Implementation of the Moment-Preserving Technique and Its Application to Thresholding , 1993, IEEE Trans. Computers.

[27]  A. Rosenfeld,et al.  A Note on the Use of Second-Order Gray Level Statistics for Threshold Selection. , 1977 .

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

[29]  Mao-Jiun J. Wang,et al.  Image thresholding by minimizing the measures of fuzzines , 1995, Pattern Recognit..

[30]  Joan Serra,et al.  Image segmentation , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[31]  Márcio Portes de Albuquerque,et al.  Image thresholding using Tsallis entropy , 2004, Pattern Recognit. Lett..

[32]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[33]  Jayaram K. Udupa,et al.  Optimum Image Thresholding via Class Uncertainty and Region Homogeneity , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Ahmed S. Abutableb.  Automatic thresholding of gray-level pictures using two-dimensional entropy , 1989 .

[35]  David G. Stork,et al.  Pattern Classification , 1973 .

[36]  Korris Fu-Lai Chung,et al.  Note on the equivalence relationship between Renyi-entropy based and Tsallis-entropy based image thresholding , 2005, Pattern Recognit. Lett..

[37]  Yang Li.  Multi-Object Segmentation Based on Curve Evolving and Region Division , 2004 .

[38]  A. D. Brink.  Thresholding of digital images using two-dimensional entropies , 1992, Pattern Recognit..

[39]  Gurdial Arora,et al.  A thresholding method based on two-dimensional Renyi's entropy , 2004, Pattern Recognit..

[40]  Qingmao Hu,et al.  On minimum variance thresholding , 2006, Pattern Recognit. Lett..