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Edge Feature Extraction Based on Digital Image Processing Techniques

机译:基于数字图像处理技术的边缘特征提取

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Edge detection is a basic and important subject in computer vision and image processing. In this paper we discuss several digital image processing techniques applied in edge feature extraction. Firstly, wavelet transform is used to remove noises from the image collected. Secondly, some edge detection operators such as Differential edge detection, Log edge detection, Canny edge detection and Binary morphology are analyzed. And then according to the simulation results, the advantages and disadvantages of these edge detection operators are compared. It is shown that the Binary morphology operator can obtain better edge feature. Finally, in order to gain clear and integral image profile, the method of bordering closed is given. After experimentation, edge detection method proposed in this paper is feasible.
机译:边缘检测是计算机视觉和图像处理中的基本和重要主题。在本文中,我们讨论了在边缘特征提取中应用的几种数字图像处理技术。首先,小波变换用于从收集的图像中移除噪声。其次,分析了一些边缘检测操作员,例如差分边缘检测,日志边缘检测,罐头边缘检测和二进制形态。然后根据仿真结果,比较这些边缘检测操作员的优点和缺点。结果表明,二进制形态操作员可以获得更好的边缘特征。最后,为了获得清晰和积分的图像简档,给出了边界闭合的方法。经过实验后,本文提出的边缘检测方法是可行的。

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