醫(yī)學(xué)圖像的亞像素點邊緣檢測

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摘要 醫(yī)學(xué)圖像的邊緣檢測是圖像分割、目標(biāo)識別、區(qū)域形狀提取等圖像分析領(lǐng)域十分重要的基礎(chǔ)。在進行醫(yī)學(xué)圖像理解和分析時，第一步往往都是邊緣檢測。目前，邊緣檢測已成為機器視覺研究領(lǐng)域最活躍的課題之一，其研究具有非常重要的理論意義和實際應(yīng)用價值。傳統(tǒng)的邊緣檢測方法的檢測精度最高只能達(dá)到一個像素級，但是，隨著科學(xué)技術(shù)的飛速發(fā)展，檢測等應(yīng)用對精確度的要求不斷提高，傳統(tǒng)的像素級邊緣檢測方法已經(jīng)不能滿足實際測量的需要，因此需要更高精度的邊緣檢測方法，即亞像素邊緣檢測方法。本文對圖像的亞像素邊緣檢測進行了深入研究，包括以下幾個方面：（1）本文詳細(xì)闡述了數(shù)字圖像邊緣檢測技術(shù)和亞像素邊緣檢測技術(shù)在國內(nèi)外取得的研究成果和發(fā)展現(xiàn)狀，論述了亞像素邊緣檢測技術(shù)的研究意義，同時，分析了亞像素邊緣檢測技術(shù)在圖像處理領(lǐng)域未來的發(fā)展趨勢。（2）對幾種經(jīng)典的像素級邊緣檢測算法進行了研究，主要包括 Roberts 算子、Sobel 算子、Prewitt 算子、Laplacian邊緣檢測算子， LOG算子， Canny算子等，并使用 Matlab 2010對這幾種算法進行仿真實驗，對比了他們的優(yōu)缺點及適用范圍。（3）對幾種常用的亞像素邊緣檢測方法進行了深入研究，包括插值法，擬合法，矩法。（4）對二次曲線擬合方法做了重點研究，先用Canny算子得到像素級邊緣，然后通過二次曲線擬合亞像素邊緣提取公式確定出圖像邊緣。最后，使用Matlab 2010實現(xiàn)本文提出的曲線擬合亞像素邊緣檢測方法，實驗結(jié)果表明：本文提出的方法能夠使檢測出的圖像邊緣達(dá)到亞像素精度。

關(guān)鍵詞 邊緣檢測 亞像素邊緣檢測 曲線擬合


Sub Pixel Edge Detection on Medical Image
Abstract Edge detection of the medical image is a very important basis in image analysis fields of image segmentation, target recognition, region shape extraction, etc. In image understanding and analyzing, the first step is always edge detection. At present, the edge detection has become one of the most active subjects in machine vision research fields, which has very important theory significance and practical application value. The detection accuracy of the traditional edge detection algorithms can only reach a pixel level. However, with the rapid development of science and technology, industrial detection and other applications for accuracy requirements is increasing. The traditional pixel level edge detection algorithms have been unable to satisfy the need of practical measurement, so we need the edge detection algorithms with higher accuracy, namely the sub pixel edge detection algorithm. In this paper, the sub pixel edge detection technology is studied deeply, and the research contents include the following several aspects: 1）In this thesis, the research achievements, the present development situation of the digital image edge detection technology and the sub pixel edge detection technology at home and abroad is described. And the research significance of the sub pixel edge detection technology is discussed. At the same time, the future development trend of the sub pixel edge detection technology in image processing field is analyzed. （2）Several classic pixel level edge detection algorithms are studied, which mainly include Roberts、 Sobel、 Prewitt、 Laplace、 LOG and Canny operator, etc. And several algorithms are simulated with MATLAB 2010. Their advantages, disadvantages and applicable scope have been Compared. (3）Several sub pixel edge detection algorithms which are commonly used are studied, including the interpolation algorithm, the curve fitting algorithm, and the moment algorithm, etc. (4) the quadratic curve fitting algorithm is studied intensively . firstly, we use the Canny operator to get the pixel level edge,and then through the quadratic curve fitting to extract the edge of the image .Finally, the algorithm has been implemented with the MATLAB 2010. The experimental results show that we can detect the edge of the digital images at sub-pixel accuracy by the proposed algorithm.
Keywords  Edge detection Sub pixel edge detection Curve fitting


目錄
第一章 緒論 1
1.1 課題背景 1
1.2 國內(nèi)外發(fā)展現(xiàn)狀 2
1.3 邊緣檢測的發(fā)展趨勢 4
1.4 課題的研究目的及意義 5
第二章 邊緣檢測算子 6
2.1 邊緣檢測技術(shù)概述 6
2.2 像素級邊緣檢測算子 6
2.2.1 Roberts邊緣檢測算子 6
2.2.2 Sobel邊緣檢測算子 7
2.2.3 Prewitt邊緣檢測算子 7
2.2.4 Laplacian邊緣檢測算子 8
2.2.5 LOG算子 8
2.2.6 Canny邊緣檢測算子 9
2.2.7 實驗結(jié)果及分析 10
第三章 亞像素邊緣檢測方法 13
3.1 亞像素定位原理 13
3.2 常用的亞像素邊緣檢測算法 14
3.2.1 插值法 14
3.2.2 擬合法 19
3.2.3 矩法 24
第四章 基于二次曲線擬合的亞像素邊緣檢測方法 29
4.1 二次擬合法的理論基礎(chǔ) 29
4.2 算法流程 31
4.3 實驗結(jié)果 32
發(fā)展與展望 34
致謝 35
參考文獻(xiàn) 36