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研究生:蔡偉成
研究生(外文):Wei-cheng Tsai
論文名稱:應用灰階影像形態學於六角影像上之邊緣偵測
論文名稱(外文):Edge Detection based on Grayscale Morphology on Hexagonal Images
指導教授:何應勤
指導教授(外文):Inn-chyn Her
學位類別:碩士
校院名稱:國立中山大學
系所名稱:機械與機電工程學系研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:119
中文關鍵詞:邊緣強化頂帽轉換邊緣偵測灰階形態學六角影像
外文關鍵詞:edge enhancementtop-hat transformedge detectiongrayscale morphologyHexagonal grid
相關次數:
  • 被引用被引用:1
  • 點閱點閱:667
  • 評分評分:
  • 下載下載:122
  • 收藏至我的研究室書目清單書目收藏:0
本研究主要探討六角影像與灰階形態學,而本研究主要分成兩部份,一為結合六角影像與灰階形態學而成的六角灰階形態學,第二,將六角灰階形態學應用於邊緣偵測與強化上發展出一套演算法。在研究過程中,由於兩者系統的不同,我們以重新取樣的方式將輸入影像轉換成六角影像,因為研究是將形態學應用在六角影像上,所以必須建立六角結構元素,研究中使用了四種尺寸的結構元素,完成形態學的運算過後並配合六角格子的顯示與排列方式,即可得到六角灰階形態學的運算結果。而六角影像的邊緣偵測與強化,我們藉由形態學中的形態梯度與提出的方法來達到效果,並對邊緣偵測影像與邊緣強化影像進行比較,最後也使用了六種不同形狀的結構元素進行邊緣偵測,並將結果進行比較,找出最適合的結構元素。

This study focuses on hexagonally sampled images and grayscale morphology. We combine hexagonal image processing and grayscale morphology to develop hexagonal grayscale morphology, and propose an algorithm to detect and enhance edges.
Hexagonal image processing consists of three important steps: conversion of hexagonally sampled images, processing, and display of processed images on simulated hexagonal grid. We construct four different sizes of hexagonal structuring elements to apply morphological operations on hexagonal images. In this study, we applied morphological gradient for edge detection and proposed algorithm for edge enhancement. Moreover, we developed six different shapes of structuring elements to find an optimum one. Finally, we assessed two methods to compare our results, and identified the best result and optimum structuring element. We expect that proposed algorithm will offer a useful tool of image processing on hexagonally sampled images.

摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 x
第一章 緒論 1
1-1 研究背景與動機 1
1-2 文獻回顧 2
1-3 研究方法 7
1-4 論文架構 9
第二章 六角取樣影像 10
2-1 對稱六角座標系統 10
2-2 矩形系統中的六角格子 12
2-3 六角格子的顯示方式 12
2-4六角格子的排列方式 14
2-4-1六角垂直交錯排列 14
2-4-2六角水平交錯排列 18
第三章 數學形態學 22
3-1灰階形態學與多規模(Multi-scale)灰階形態學 22
3-1-1膨脹與侵蝕 22
3-1-2閉合與斷開 24
3-2 灰階形態學的邊緣偵測運算 26
3-3 頂帽轉換 28
第四章 六角灰階形態學 30
4-1 六角結構元素 30
4-2 六角灰階形態學運算 33
4-2-1膨脹 33
4-2-2侵蝕 34
4-2-3斷開 35
4-2-4閉合 36
4-3 六角灰階形態學的形態梯度 37
4-4 六角灰階形態學的影像強化 38
4-5 應用於六角影像上的邊緣偵測與強化方法 42
第五章 結果與比較 44
5-1影像轉換 44
5-2 六角灰階形態學 45
5-2-1膨脹 46
5-2-2侵蝕 47
5-2-3閉合 48
5-2-4斷開 49
5-2-5形態梯度 50
5-2-6頂帽轉換 52
5-3 多規模六角灰階形態學 55
5-3-1膨脹 55
5-3-2侵蝕 55
5-3-3閉合 64
5-3-4斷開 64
5-3-5形態梯度 73
5-3-6頂帽轉換 73
5-4 邊緣強化 94
5-5以不同結構元素進行邊緣偵測 96
5-6 結果比較 98
第六章 結果與討論 101
6-1 結論 101
6-2 討論 102
Reference 103

[1] Middleton, L. and Sivaswamy J., 2005, “Hexagonal image processing: a practical approach,” Springer-Verlag New York Inc.
[2]Golay, M., 1969, “Hexagonal parallel pattern transformation,” IEEE Transaction on computers, 18(8), pp. 733-740.
[3]Deutsch, E. S., 1972, “Thinning algorithm on rectangualr, hexagonal, and triangular arrays,” Communications of the ACM, 15(9), pp. 827-837.
[4]Mersereau, R. M., 1979, “The processing of Hexagonally Sampled Two-Dimensional Signals,” Proceedings of the IEEE, 67(6), pp. 930-949.
[5]Staunton, R., 1989, “The design of hexagonal sampling structures for image digitization and their use with local operators,” Image and Vision Computing, 7(3), pp. 162-166.
[6]Staunton, R. C., 1996, “A analysis of hexagonal thinning algorithms and skeletal shape representation,” Pattern Recognition, 29(7), pp. 1131-1146.
[7] Kuijper, A., 2004, “On detecting all saddle points in 2D images,” Pattern Recognition Letters, 25(15), pp.1665-1672.
[8]Middleton, L. and Sivaswamy J., 2001, “Edge detection in a hexagonal-image processing framwork,” Image and Vision Computing, 19(14), pp. 1071-1081.
[9] He, X., Jia, W., Hur, N., Wu, Q., Kim, J. and Hintz, T., 2006, “Bilateral Edge Detection on a Virtual Hexagonal Structure,” Lecture Notes in Computer Science, 4292, pp. 176-185.
[10] Her, I. and Yuan, C. T., 1994, “Resampling on a Pseudohexagonal Grid,” CVGIP. Graphical Models and Image Processing, 56(4), pp.336-347.
[11]Liu, L. and Dai, T. S., 2011, “A Reliable Fingerprint Orientation Estimation Algorithm,” Journal of Information Science and Engineering, 27(1), pp. 353-368.
[12] Her, I., 1995, “Geometric Transformations on the Hexagonal Grid,” IEEE Transactions on Image Processing, 4(10), pp, 1212-1222.
[13]Ville, D. V. D., Walle, E.V. D., Philips, W. and Lemahieu, I., 2002, “Image Resampling Between Orthogonal and Hexagonal Lattices,” IEEE Proceeding on Image Processing, 3, pp. 389-392.
[14]Ville, D. V. D., Blu, T. and Unser, M, 2003, “Recursive Filtering for Splines on Hexagonal Lattices,” International Conference on Acoutics, Speech, and Signal Processing, 3, pp. 301-304.
[15]Knaup, M., Steckmann, S., Bockenbach, O. and Kachelrieb, M., 2007, “CT Image Reconstruction using Hexagonal Grids,” IEEE Nuclear Science Symposium Conference Record, 4, pp. 3074-3076.
[16] He, X., Li, J. and Hintz, T., 2007, “Comparison of Image Conversion Between
Square Structure and Hexagonal Structure,” International Conference on Advanced concepts for intelligent vision systems , 4678, pp.262-273.
[17] Faille, F. and Petrou, M., 2010, “Invariant image reconstruction from irregular
samples and hexagonal grid splines,” Image and Vision Computing, 28, pp. 1173-1183.
[18]Shima, T., Sugimoto, S. and Okutomi, M., 2010, “Comparison of Image Alignment on Hexagonal and Square Lattices,” Proceedings of 2010 IEEE 17th International Conference on Image Processing, pp.141-144.
[19] Staunton, R. C. and Storey, N., 1990, “A Comparison Between Square and Hexagonal Sampling methods for Pipeline Image Processing,” Proc. Of Optics, Illumination, and Image Sensing for Machine Vision IV on SPIE, 1194, pp. 142-151.
[20]Fitz, A. P. and Green, R. J., 1996, “Fingerprint Classification using a Hexagonal Fast Fourier Transform,” Pattern Recognition, 29(10), pp.1587-2597.
[21] Senthilnayaki, M., Veni, S. and Narayanan Kutty, K. A., 2006, “Hexagonal Pixel
Grid Modeling for Edge Detection and Design of Cellular Architecture for Binary Image Skeletonization,” Annual India Conference, pp. 1-6.
[22] Gardiner, B., Coleman, S. and Scotney, B., 2007, “A Design Procedure for Gradient Operators on Hexagonal Images,” International Machine Vision and Image Processing Conference, pp. 47-54.
[23] He, X., Jia, W. and Wu, Q., 2008, “An Approach of Canny Edge Detection with Virtual Hexagonal Image Structure,” International Conference on Control, Automation, Robotics and Vision, pp.167-172.
[24]Shima, T., Saito, S. and Nakajima, M., 2010, “Design and Evakuation of More Accurate Gradient Operators on Hexagonal Lattices,” IEEE Transcations on Pattern Analysis and Machine Intelligence, 32(6), pp.961-973.
[25]Serra, J., 1986, “Introducation to Mathematical Morphology,” Computer Vision, Graphics, and Image Processing, 35(3), pp. 283-305.
[26] Peli, T., 1982, “A Study of Edge Detection Algorithms,” Computer Graphics
and Image Processing, 20(1), pp. 1-21.
[27] Ruberto, C., Dempster, A., Khan, S. and Jarra, B., 2000, “Segmentation of Blood Images Using Morphological Operators,” International Conference on Pattern Recognition, 3, pp. 397-400.
[28] Mukhopadhyay, S. and Chanda, B., 2000, “A multiscale morphological approach
to local contrast enhancement,” Signal Processing, 80, pp.685-696.
[29] Tripathi, N. K. and Gokhale, K. V. G. K., 2000, “Directional morpphological image transforms for linement extraction from remotely sensed images,” International Journal of Remote sensing, 21(17), pp.3281-3292.
[30]Chen, L., Zheng, H., Li, L., Xie, P. and Liu, S., 2007, “Near-infrared Dorsal
Hand Vein Image Segmentation by Local thresholding Using Grayscale Morphology,” International Conference on Bioinformatics and Biomedical Engineering, pp.868-871.
[31] Jeong, T. G., Joo, H. and Rew, K. H., 2008, “Morphological Segmentation of Markings for Inspection of IC Packages Under Complex Backgrounds,” International Conference on Control, Automation and Systems, pp. 1976-1980.
[32]Santhaiah Ch., Babu, G. A. and Rani, M. U., 2009, “Gray-level Morphological Operations for Image Segmentation and Tracking Edges on Medical Applications,” International Journal of Computer Science and Network Security, 9(7), pp.131-136.
[33]Li, T. G., Wang, S. P. and Zhao, N., 2009, “Gray-scale edge detection for gastric tumor pathologic cell images by morphological analysis,” Computers in Biology and Medicine, 39, pp.947-952.
[34]Zhong, Y. W., 2009, “Mathematical Morphology Based Enhancement for
Chromosome Images,” International Conference on Bioinformatics and Biomedical Engineering, pp. 1-3.
[35]Kaur, B., Garg, A. and Kaur, A., 2010, “Mathematical Morphological Edge Detection For Remote Sensing Images,” International Joural of Electronics and Communication Technology, 1(1), pp.29-33.
[36] Zhang, Y., Su, X. and Liu, Z., 2010, “A Multi-structuring Elements Edge
Detection Method Based on Gray-scale Morphology of Parameter Image for Rotating Machinery,” International Congress on Image and Signal Processing, 3, pp. 1067-1071.
[37]Bai, X. and Zhou, F., 2010, “Analysis of different modified top-hat transformations based on structuring element construction,” Signal Processing, 90, pp. 2999-3003.
[38]Bai, X., Zhou, F. and Xue, B., 2010, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Physics & Technology, 54, pp. 61-69.
[39]Bai, X., Zhou, F. and Xue, B., 2011, “Fusion of infrard and visual images through region extraction by using multi scale center-surround top-hat transform,” Optics Express, 19(9), pp. 8444-8457.
[40] Su, T. C., Yang, M. D., Wu, T. C. and Lin, J.Y., 2011, “Morphological segmentation based on edge detection for sewer pipe defects on CCTV images,” Expert Systems with Applications, 38, pp. 13094-13114.
[41] Li, B., Zhang, P. L., Wang, Z. J., Mi, S. S. and Zhang, Y. T., 2011, “Gear fault
detection using morphological filters,” Measurement, 44(10), pp. 2078-2089.
[42]Her, I., 1993, “A symmetrical Coordinate Frame on the Hexagonal Grid for Computer Graphics and Vision,” ASME Journal of Mechanical Design, 115(3), pp. 447-449.
[43] 許明進, 2001, 在六角格子裝置上顯示文字及圖形的基本架構, 碩士論文, 國立中山大學機械與機電工程研究所
[44]Maragos, P., 1989, “Pattern spectrum and multiscale shape representation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), pp.701-716.
[45] Li, B., Zhang, P. L., Wang, Z. J., Mi, S. S. and Zhang, Y. T., 2011, “Gear fault detection using multi-scale morphological filters,” Measurement, 44, pp. 2078-2089.
[46]Lai, R., Yang, Y. T., Wang, B. J. and Zhou, H. X., 2010, “A quantitative measure
based infrared enhancement algorithm using plateau histogram,” Optics Communications, 283(21), pp. 4283-4288.
[47]Kaufmann, A., 1975, “Introducation to the Theory of Fuzzy,” Academic Press.

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