臺灣博碩士論文加值系統

雖然以模擬浸入為依據的分水嶺分割法已被廣泛應用於影像分割，但由於在彩色影像上，我們很難定義色彩與色彩間的高低次序關係，所以這個方法很少被應用於彩色影像上。在這篇論文中，我們利用以梯度向量為依據的分水嶺分割法提出以彩色視覺向量為依據的分水嶺分割法藉以分割彩色影像。我們提出的方法採用最能模擬人類視覺效果的HVC色彩空間以及NBS (National Bureau of Standards) 色彩差距度量法， 所以分割的結果和人類視覺效果相似，令人滿意。

Watershed based on immersion simulations is extensively used in image segmentation, but it is rarely applied in color images because in a color image, it is hard to find a variable to decide the order relation. In this paper, we improve the watershed method based on gradient vectors and propose a new watershed method based on color perceptual vector in order to implement watershed on color images. This method makes use of HVC, the best color space in simulating the human color vision, and National Bureau of Standards (NBS) color distance so that the segmentation result performs satisfactory human visual discrimination. The empirical outcomes show that the HVC color space is better than the LUV color space; moreover, the resulting watershed boundaries identify perceptually different regions.

摘 要i
ABSTRACTii
ACKNOWLEDGEMENTSiii
TABLE OF CONTENTSiv
LIST OF FIGURESvi
LIST OF TABLESvii
CHAPTER 1INTRODUCTION1
CHAPTER 2WATERSHED METHODS3
2.1Watersheds Using Immersion Simulation3
2.2Watersheds Using Gradient Vectors4
2.3Over-Segmentation Problem5
2.4HVC Color Space6
2.5Color Watershed8
CHAPTER 3COLOR WATERSHED BASED ON HUMAN PERCEPTION10
3.1Detection of Smooth Regions 11
3.2Color Watershed Transform Based on Human Perception13
3.3Region Growing15
3.4Merging Similar Regions17
CHAPTER 4EXPERIMENT RESULTS18
4.1Comparison with Different Merging Threshold Values18
4.2Comparison with Different Color Spaces19
CHAPTER 5CONCLUSIONS23
REFERENCES24

[1]N. R. Pal and S. K. Pal, “A review on image segmentation techniques,” Pattern Recognition, vol. 26, no. 9, pp. 1277-1294, Mar. 1993.
[2]K. Haris and S. N. Efstratiadis, “Hybrid image segmentation using watersheds and fast region merging,” IEEE Trans. Image Processing, vol. 7, no. 12, pp. 1684-1699, Dec. 1998.
[3]I. E. Pratikakis, H. Sahli, and J. Cornelis, “Low level image partitioning guided by the gradient watershed hierarchy,” Signal Processing, vol. 75, no. 2, pp. 173-195, 1999.
[4]L. Vincent and P. Soille, “Watersheds in digital spaces: An efficient algorithm based on immersion simulations,” IEEE Trans. Pattern Anal. Machine Intell., vol. 13, no. 6, pp. 583-598, June 1991.
[5]J. M. Gauch, “Image segmentation and analysis via multiscale gradient watershed hierarchies,” IEEE Trans. Image Processing, vol. 8, no. 1, pp. 69-79, Jan. 1999.
[6]F. Meyer and S. Beucher, “Morphological segmentation,” J. Vis. Commun. Image Represent., vol. 1, pp. 21-46, Sep. 1990.
[7]L. Shafarenko, M. Petrou, and J. Kittler, “Histogram-based segmentation in a perceptually uniform color space,” IEEE Trans. Image Processing, vol. 7, no. 9, pp. 1354-1358, Sep. 1998.
[8]X. Wan and C. C. Kuo, “A new approach to image retrieval with hierarchical color clustering,” IEEE Trans. Circuits Syst. Video Technol., vol. 8, no. 5, Sep. 1998.
[9]F. W. Billmeyer and M. Saltzman, Principles of Color Technology, 2nd Ed., New York: Wiley, 1981.
[10]S. C. Pei and C. M. Cheng, “Extracting color features and dynamic matching for image data-base retrieval,” IEEE Trans. Circuits Syst. Vedio Technol., vol. 9, no. 3, pp. 501-512, Apr. 1999.
[11]J. Hafner, H. S. Sawhney, W. Equitz, M. Flickner, and W. Niblack, “Efficient color histogram indexing for quadratic form distance functions,” IEEE Trans. Pattern Anal. Machine Intell., vol. 17, no. 7, pp. 729-736, July 1995.
[12]M. Bartkowiak and M. Domanski, “Vector median filters for processing of color images in various color spaces,” in Proc. IEE Conf. Image Processing and Its Applications, 1995, pp. 4-6.
[13]Y. Gong, G. Proietti, and C. Faloutsos, “Image indexing and retrieval based on human perceptual color clustering,” in Proc. of IEEE Conf. Computer Vision and Pattern Recognition, Santa Barbara, CA, 1998, pp. 578-583.
[14]M. Kim et al., “A VOP generation tool: Automatic segmentation of moving objects in image sequences based on spatio-temporal information, ” IEEE Trans. Circuits Syst. Video Technol., vol. 9, no. 8, pp. 1216-1226, Dec. 1999.
[15]L. Shafarenko, M. Petrou, and J. Kittler, “Automatic watershed segmentation of randomly textured color images,” IEEE Trans. Image Processing, vol. 6, no. 11, pp. 1530-1544, Nov. 1997.
[16]R. C. Gonzales and P. Wintz, Digital Image Processing. 2nd Ed., Reading, MA: Addison-Wesley, 1987.