Recursive Algorithms for Image Segmentation Based on a Discriminant Criterion

Authors: Bing-Fei Wu, Yen-Lin Chen, Chung-Cheng Chiu

Abstract:

In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1

Keywords: image segmentation, multilevel thresholding, clustering, discriminant analysis

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1081229

References:

[1] Sahoo P.K., Soltani S., Wong A.K.C., Chen Y.C., "A survey of thresholding techniques", Computer Vision, Graphics and Image Processing, vol. 41, pp. 233-260, 1988.
[2] Otsu, N., "A threshold selection method from gray-level histograms", IEEE Transactions on Systems, Man and Cybernetics, vol. SMC-9, pp. 62- 66, 1979.
[3] Kapur, J., Sahoo P.K., Wong A.K.C., "A new method for gray-level picture thresholding using the entropy of the histogram", Computer Vision, Graphics and Image Processing, vol. 29, pp. 273-285, 1985.
[4] Kittler, J. and Illingworth, J., "Minimum Error Thresholding", Pattern Recognition, vol. 19, pp. 41-47, 1986.
[5] Li, C.H. and Lee, C.K., "Minimum cross entropy thresholding", Pattern Recognition, vol. 26, pp. 617-625, 1993.
[6] Tsai W.H., "Moment-preserving thresholding: A new approach", Computer Vision, Graphics and Image Processing, vol. 29, pp. 277-393, 1985.
[7] Reddi, S.S., Rudin, S. F., and Keshavan, H.R., "An optimal multiple threshold scheme for image segmentation", IEEE Transactions on Systems, Man and Cybernetics, vol. SMC-14, pp. 661-665, 1984.
[8] Cheng, H.D., Chen, Y.H., and Sun, Y., "A Novel Fuzzy Entropy Approach to image enhancement and thresholding", Signal Processing, vol. 75, pp. 277-301, 1999.
[9] Tsai, D.M., "A fast thresholding selection procedure for multimodal and unimodal histograms", Pattern Recognition Letters, vol. 16(6), pp. 653- 666, 1995.
[10] Cao L., Shi Z.K. and Cheng E.K.W., "Fast automatic multilevel thresholding method", Electronics Letters, vol. 38(16), pp. 868-870, 2002.
[11] Cheriet M., Said J.N., and Suen C.Y., "A recursive thresholding technique for image segmentation", IEEE Transactions on Image Processing, vol. 7(6), pp. 918-921, 1998.
[12] Levine, M.D. and Nazif, A.M., "Dynamic measurement of computer generated image segmentation", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 7, pp. 155-164, 1985.