Minimum cross entropy thresholding

Li, C. H.; Lee, C. K.

Affiliations

¹Department of Electronic Engineering, Hong Kong Polytechnic, Hung Hom, Hong Kong

Abstract and keywords

The threshold selection problem is solved by minimizing the cross entropy between the image and its segmented version. The cross entropy is formulated in a pixel-to-pixel basis between the two images and a computationally attractive algorithm employing the histogram is developed. Without making a priori assumptions about the population distribution, this method provides an unbiased estimate of a binarized version of the image in an information theoretic sense.

Keywords: Thresholding; Image segmentation; Minimum cross entropy; Maximum entropy method

Links

DOI: 10.1016/0031-3203(93)90115-D

WoS: A1993LD88100014

Cited Works (7)

Year	Entry
1986	Kittler J, Illingworth J. Minimum error thresholding. Patt Recogn. 1986;19(1):41-47.
1980	Pun T. A new method for grey-level picture thresholding using the entropy of the histogram. Signal Process. July 1980;2(3):223-237.
1985	Kapur JN, Sahoo PK, Wong AKC. A new method for gray-level picture thresholding using the entropy of the histogram. Comput Vis Graph Image Proc. 1985;29(3):273-285.
1979	Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Sys Man Cyb. 1979;9(1):62-66.
1989	Wong AKC, Sahoo PK. A gray-level threshold selection method based on maximum entropy principle. IEEE Trans Sys Man Cyb. 1989;19(4):866-871.
1988	Sahoo PK, Soltani S, Wong AKC. A survey of thresholding techniques. Comput Vis Graph Image Proc. 1988;41(2):233-260.
1981	Pun T. Entropic thresholding, a new approach. Comput Graph Image Proc. July 1981;16(3):210-239.

Cited By (9)

Year	Entry
2010	Hammouche K, Diaf M, Siarry P. A comparative study of various meta-heuristic techniques applied to the multilevel thresholding problem. Eng Appl Artificial Intell. 2010;23(5):676-688.
2016	Hussein WA, Sahran S, Abdullah SNHS. A fast scheme for multilevel thresholding based on a modified bees algorithm. Knowledge-Based Syst. June 1, 2016;101:114-134.
2004	Lievers WB, Pilkey AK, Lloyd DJ. Using incremental forming to calibrate a void nucleation model for automotive aluminum sheet alloys. Acta Mater. June 7, 2004;52(10):3001-3007.
2008	Hammouche K, Diaf M, Siarry P. A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation. Comput Vis Image Und. 2008;109(2):163-175.
2004	Lievers WB, Pilkey AK. An evaluation of global thresholding techniques for the automatic image segmentation of automotive aluminum sheet alloys. Mater Sci Eng. September 15, 2004;A381(1-2):134-142.
1997	Sahoo P, Wilkins C, Yeager J. Threshold selection using Renyi's entropy. Patt Recogn. January 1997;30(1):71-84.
2004	Sahoo PK, Arora G. A thresholding method based on two-dimensional Renyi's entropy. Patt Recogn. June 2004;37(6):1149-1161.
2022	Luengo J, Moreno R, Sevillano I, Charte D, Peláez-Vegas A, Fernández-Moreno M, Mesejo P, Herrera F. A tutorial on the segmentation of metallographic images: taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges. Inf Fusion. February 1, 2022;78:232.
2011	Sloan ADC. The Role of Non-Ferritic Phase in the Micro-Void Damage Accumulation and Failure of Dual-Phase Steels [Master's thesis]. Queen's University; September 2011.