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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/35223

    Title: A statistical approach to boundary-based corner detection
    Other Titles: 基於統計分析之邊界轉折點偵測方法
    Authors: 陳俊文;Chen, Chun-wen
    Contributors: 淡江大學資訊工程學系博士班
    洪文斌;Horng, Wen-bing
    Keywords: 轉折點偵測;曲率測量;最佳化方法;門檻值估計;Corner detection;curvature measure;optimization method;threshold estimation
    Date: 2009
    Issue Date: 2010-01-11 06:13:35 (UTC+8)
    Abstract: 影像上的轉折點具有幾何轉換(如平移、旋轉、縮放…等)之不變性,在電腦視覺的研究領域,一直都是重要的辨識特徵。近年來,偵測邊界轉折點已被廣泛應用在多邊形逼近、曲線密合、自動光學檢測、影像切割、影像校正與形變、物體辨識、運動速寫等各方面。偵測邊界轉折點時,需先將影像主體自背景分離出來,接著在物體邊界上找出曲率變化明顯的轉折點位置。然而影像在數位化過程,因量化處理與雜訊干擾,往往造成邊界上的鋸齒現象,影響偵測邊界轉折點的成效。
    Corners have been one of the most important features in computer vision since they are invariant to geometric transformations, such as translation, rotation and scaling. Boundary-based corner detectors, segmenting objects from an image first and then locating the discontinuities on the object boundaries, have been widely applied to polygonal approximation, spline curve fitting, automated visual inspection, image segmentation, image registration, shape morphing, handwriting/environment/object recognition, motion sketch, etc. The accuracy of corner detection on boundaries is primarily influenced by quantization and noises.
    In this thesis, we propose a robust boundary-based corner detection algorithm for diverse images. The algorithm is composed of three components: a new measure of significance based on the eigenvalues of covariance matrices, threshold estimation of the measure of significance of any angle, and an optimization procedure based on a discriminant criterion for determining the length of region of support. The experimental results show that our algorithm outperforms other methods, even in the noisy samples. These robust results are due to not only the reliable measure of significance but also the discriminating optimization procedure of our algorithm.
    Appears in Collections:[資訊工程學系暨研究所] 學位論文

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