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Wrist bone feature recognition system for bone contour extraction method

Author: WangHong
Tutor: LiYiMin
School: Kunming University of Science and Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Image Processing Medical Imaging Bone identification Edge Extraction Snake model
CLC: R318
Type: Master's thesis
Year: 2005
Downloads: 81
Quote: 1
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Abstract


The task of this project is the use of a variety of edge detection technology for bone recognition system has been split out of the characteristics of the bone edge extraction method. In this issue try a variety of traditional edge detection method. And how will combine high-level knowledge Snake model is applied to the subject of. After obtaining characteristics of bone, to the edges of the target object to be tested later extracted as shape analysis and decision aspects basis. In the image, the edge information is very important and useful. By extracting the edge of a continuous high-level access to some of the target information such as target length, width, area, or ratio of the size. These information the identification of post. Edge is the result of a discontinuous gray value, mainly for the local feature discontinuities image is the image brightness function change drastically location. The traditional methods of differential edge extraction method, linear filtering. In the differential method, the original image pixel is a small neighborhood to construct edge detection operator. However, using this method, the first edge detection exists between accuracy and noise filtering contradiction if improving detection accuracy, the noise generated pseudo edges will lead to unreasonable contours; if improved noise immunity, it will produce contour missed and position deviation; secondly there is the detected edges discontinuity. Thus, linear filtering methods proposed. In this method, in a certain range for the smoothing filter to eliminate noise interference, and detection occurs at the edges of the respective scales. Although this method is better balance between noise immunity and detection accuracy, but still fundamentally overcome the contradiction between the two. Snake model is an interactive, top-down edge extraction model, the model using a certain level of knowledge, to focus on and near the edge of the edge itself, thereby improving the reliability and accuracy of edge detection, on the edge of the object can cross the discontinuous region to obtain a complete edge. Snake model based on the assumption: the border is continuous and smooth. Therefore, the image can be used to approximate the position and shape of objects. Snake model first through the ability to identify people in the vicinity of the edge to be extracted several control points and connected into a continuous curve. Fully utilizing the image information, external constraints and the curve continuity and smoothness constraints define an energy function, the role of each control point, the control points of the energy is based on the Snake shape and pattern of the control points of the location determination, the control point to the area of ??reduced energy function moves, and finally when the energy function is no longer reduced, ie, to obtain the required target edge extraction. Snake model can guarantee to obtain a continuous edge, and is not sensitive to image noise and contrast. However, the basic algorithm Snake model in practical applications, there are a lot of questions: initial contour election

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CLC: > Medicine, health > Basic Medical > Medical science in general > Biomedical Engineering
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