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Image segmentation plays a very important role in many image understanding and computer vision techniques. Over the last few decades image segmentation techniques have been advanced significantly, though a few quantitative evaluation techniques have been proposed. Most of the segmentation evaluation techniques are largely subjective that means the evaluation is done visually, intuitively or qualitatively...
Online measurement of wheel set wear parameters is important for train safety. The acquisition and processing of wheel set profile image is a key problem in online measuring based on machine vision. Appropriate threshold segmentation is needed to extract clear wheel set profile curve from varying background. Otsu algorithm is the traditional optimal threshold method, which is popular and efficient,...
Images segmentation is an important issue for many applications as pattern recognition and computer vision. Thresholding is an important and fast technique used in most applications. Gaussian Otsu's method is a thresholding technique based on between class variance. Gamma distribution models data more than Gaussian distribution. In this paper, we developed a new formula using Otsu's method for estimating...
We present a new, geometric approach for determining the probability density of the intensity values in an image. We drop the notion of an image as a set of discrete pixels, and assume a piecewise-continuous representation. The probability density can then be regarded as being proportional to the area between two nearby isocontours of the image surface. Our paper extends this idea to joint densities...
Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise...
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