Starfruit Image Segmentation Based on YCbCr Color Space

R. Amirulah, M. Mokji, Z. Ibrahim, U. U. Sheikh
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引用次数: 4

Abstract

Segmentation in a classification system plays an important role as it will determine the region of interest for the classification. In this work, the segmentation of star fruit is performed in YCbCr color space. Because of the background of the image to be classify has 2 different colors, which are black and white, the segmentation is obtained using a fixed threshold value for the Cb component. This is because the value for Cb is equivalent in black, white or gray scale pixels. By fixing the threshold for Cb component, the region of interest (ROI) can easily be determined and then proceeded to the classification process. The results in this paper show that the ROI can be determined completely by this method.
基于YCbCr颜色空间的杨桃图像分割
分割在分类系统中起着重要的作用,因为它决定了分类的兴趣区域。在这项工作中,杨桃的分割是在YCbCr颜色空间中进行的。由于待分类图像的背景有两种不同的颜色,分别是黑色和白色,因此对Cb分量采用固定的阈值进行分割。这是因为Cb的值在黑色、白色或灰度像素中是相等的。通过确定Cb分量的阈值,可以很容易地确定感兴趣区域(ROI),然后进行分类过程。本文的研究结果表明,该方法可以完全确定投资回报率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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