Segmentation of small objects in color images
A method for effective segmentation of small objects in color images is presented. It can be used jointly with region growing algorithms. Segmentation of small objects in color images is a difficult problem because their boundaries are close to each other. The proposed algorithm accurately determines the location of the boundary points of closely located small objects and finds the skeletons (seed regions) of those objects. The method makes use of conditions obtained by analyzing the change of color characteristics of the edge pixels along the direction that is orthogonal to the boundaries of adjacent objects. These conditions are generalized for the case of the well-known class of color images having misregistration artifacts. If high-quality seed regions are available, the final segmentation can be performed using one of the region growing methods. The segmentation algorithm based on the proposed method was tested using a large number of color images, and it proved to be very efficient.
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- 3.Lucchese, L. and Mitra, S.K., Color Image Segmentation: A State-of-the-Art Survey, Proc. of the Indian National Sci. Academy (INSA_A), Image Process. Vision, Pattern Recognit., 2001, vol. 67A, no. 2, pp. 207–221.Google Scholar
- 4.Skarbek, W. and Koschan, A., Colour Image Segmentation—A Survey, Technical Report of the Berlin Technical University, Berlin, 2004.Google Scholar
- 5.Plataniotis, K.N. and Venetsanopoulos, D.T., Color Image Processing and Applications (Digital Signal Processing), Springer, Berlin, 2000.Google Scholar
- 6.R. C. Gonzalez and R. E. Woods, Digital Image Processing (Prentice-Hall, Upper Saddle River, N.J., 2002).Google Scholar
- 12.Beucher, S., The Watershed Transformation Applied to Image Segmentation, in Proc. 10th Pfefferkorn Conf. on Signal and Image Processing in Microscopy and Microanalysis, Cambridge, UK, 1991, Scanning Microscopy Int., 1996, Suppl. 6, pp. 299–314.Google Scholar
- 21.Beucher, S. and Meyer, F. The Morphological Approach to Segmentation: The Watershed Transformation, Mathematical Morphology in Image Processing, Dougherty, E.R., Ed., New York: Marcel Dekker, 1992, pp. 433–481.Google Scholar
- 25.Digital Color Imaging Handbook, Sharma, G., Ed., Boca Raton, Fl.: CRC, 2003, ch. 7, pp. 491–558.Google Scholar