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Adaptive Sobel Operator and Its Uses

机译:自适应Sobel操作员及其用途

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摘要

As we known, a main problem in image classification and explanation is the segmentation of image. Use of the boundary contour rather than most of other prepreocessed data help in simpler image representation, registration, and identification. Thus the problems of edge detection and contour following have been widely addressed with proposed solutions ranging over simple thresholding, signal processing, filtering techniques, and definition of admissible edge profile function, etc. Most of these techniques seem to be comlex and time consuming. To solve the conflict between noise and time consume, this paper presents a fast method for detecting the contour of images. It consists of three steps: first, reduce the image noise by using a high frequency noise sensitive smoothing operator; second, detect the edge by using an algorithm based on modified Soble operator; and third, follow the boundary contour and determine the area of interesting in the image. The results of expriment show that the mehtod is fast and accurate.
机译:如我们所知,图像分类和解释中的主要问题是图像的分割。使用边界轮廓而不是大多数其他预处理数据有助于更简单的图像表示,注册和识别。因此,边缘检测和轮廓的问题已被广泛寻址的提出的解决方案,该解决方案在简单的阈值,信号处理,滤波技术和可允许的边缘轮廓功能的定义等上进行范围,大多数这些技术似乎是焦点和耗时的。为了解决噪声和时间消耗之间的冲突,本文提出了一种用于检测图像轮廓的快速方法。它由三个步骤组成:首先,使用高频噪声敏感的平滑操作员降低图像噪声;其次,通过使用基于改进的索尼算子的算法来检测边缘;第三,遵循边界轮廓并确定图像中有趣的区域。 expring的结果表明Mehtod快速准确。

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