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Research on Image Characteristic Extraction Algorithm Based on Edge and Corner

Author: PanZuo
Tutor: JingXiaoJun
School: Beijing University of Posts and Telecommunications
Course: Communication and Information System
Keywords: To keep the details of image filtering Mathematical Morphology Edge Detection Corner detection
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 610
Quote: 2
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Abstract


With the advancement of science and technology, human society has entered a new digital era. Image as an important information carrier, its effective research and represents, in a digital information processing has a very important significance. The image features as image annotation attributes can be used to do, and often become a hot and difficult research areas of digital image, correctly extract the characteristics of the image segmentation, image understanding, pattern recognition and computer vision research in the field of basic and key premise. In many image feature, especially the edges and corners of the image point is most important, because they can be more complete depicts the characteristics of the image. The edges of the image can be defined as the region of the discontinuity of the gradation of an image, texture, color and other local features, corner points belong to the edge of the most specific class point, which is the endpoint of the sharp edges, corners often is defined as the image boundary curvature is high enough or sufficiently obvious point of the curvature change. The image edge detection and corner detection image feature extraction areas of the most important research content, and is also the basis of the follow-up of advanced image processing. The article first detailed comparison of the strengths and weaknesses of the various classic edge detection algorithm and SUSAN corner detection algorithm, the lack of the traditional algorithm in the presence of weak filtering or filtering mechanisms, the lack of a way to strengthen the fuzzy image features filtered to reduce useless manner using Multiscale image feature multiple response and reduced by the noise caused by the image feature false detection. For the above shortcomings, the paper proposes a series of new solutions, the main work includes the following three aspects: 1) the poor traditional algorithm for image filtering effect, put forward a set of three preserving image details improved filtering algorithm (CS-LAMF ASF-M, CS-GF), respectively, to be dealt with separately and pepper noise, Gaussian noise and mixed noise and, as far as possible, to reduce the image feature fuzzy phenomenon. 2) the introduction of the theory of mathematical morphology, its calculation of the filtered image feature enhanced treatment, combined with a new set of filtering algorithm is proposed based the Canny noise type adaptive edge detection algorithm. 3) learn from the Harris corner detection algorithm design thinking, and combines this paper a new pseudo corner template matching detection method, adaptive maximum response calculated the USAN threshold and initial corner / lower limit of the to suppress three new mechanisms to the adaptive corner detection algorithm based on an improved SUSAN comprehensive improvement. Can be seen by the end of this article comparative experiments effectively improve the filtering effect, a new filtering mechanism to maintain the details of the image features in many types of noise; edge detection algorithm based on adaptive Canny noise type far more than the traditional algorithm detects effect the environment has also maintained a good real-time performance; corner detection algorithm based on the SUSAN improved adaptive both to provide better detection effect.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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