Responsive image
博碩士論文 etd-0829112-160819 詳細資訊
Title page for etd-0829112-160819
論文名稱
Title
應用灰階影像形態學於六角影像上之邊緣偵測
Edge Detection based on Grayscale Morphology on Hexagonal Images
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
119
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2012-07-24
繳交日期
Date of Submission
2012-08-29
關鍵字
Keywords
邊緣強化、頂帽轉換、邊緣偵測、灰階形態學、六角影像
edge enhancement, top-hat transform, edge detection, grayscale morphology, Hexagonal grid
統計
Statistics
本論文已被瀏覽 5639 次,被下載 2184
The thesis/dissertation has been browsed 5639 times, has been downloaded 2184 times.
中文摘要
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。
Abstract
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.
目次 Table of Contents
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
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