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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >A FUZZY REGION GROWING APPROACH FOR SEGMENTATION OF COLOR IMAGES
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A FUZZY REGION GROWING APPROACH FOR SEGMENTATION OF COLOR IMAGES

机译:彩色图像分割的模糊区域增长方法

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摘要

Segmentation is one of the most important preprocessing steps towards pattern recognition and image understanding and a significant step towards image compression and coding. With detecting edges, most of the large segments can be found and separated from others by edge pixels. It is, however, the pixels on edge locations or those in high detailed areas whose association to adjacent segments must be found A pixel can be a part of the closest segment or in association with the neighboring pixels from a new smaller segment. In this paper, two segmentation algorithms are presented. One is used for fine segmentation towards compression and coding of images and the other for coarse segmentation towards other applications like object recognition and image understanding. Edge detection and region growing approaches are combined to find large and crisp segments for coarse segmentation. Segments can grow or expand based on two fuzzy criteria. The fuzzy region growing and expanding approaches presented here use histogram tables for fine segmentation. The procedures introduced here can be used in any order or combination to yield the best result for any particular application or image type. (C) 1997 Pattern Recognition Society. [References: 36]
机译:分割是实现模式识别和图像理解的最重要预处理步骤之一,也是迈向图像压缩和编码的重要一步。通过检测边缘,可以找到大多数大片段,并通过边缘像素将其与其他片段分开。但是,必须找到边缘位置上的像素或高细节区域中的像素,这些像素必须与相邻段相关联。像素可以是最近段的一部分,也可以与新的较小段中的相邻像素关联。本文提出了两种分割算法。一种用于对图像进行压缩和编码的精细分割,另一种用于对其他应用(如对象识别和图像理解)的粗略分割。边缘检测和区域增长方法相结合,以找到较大且清晰的片段,以进行粗略的分割。细分可以基于两个模糊标准来增长或扩展。此处介绍的模糊区域增长和扩展方法使用直方图表进行精细分割。此处介绍的过程可以按任何顺序使用或组合使用,以针对任何特定应用程序或图像类型产生最佳效果。 (C)1997模式识别学会。 [参考:36]

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