Agricultural image target segmentation based on fuzzy set

文献类型： 外文期刊

第一作者： Gao, Ronghua

作者： Gao, Ronghua;Wu, Huarui;Gao, Ronghua;Wu, Huarui;Gao, Ronghua;Wu, Huarui

作者机构：

关键词： Target segmentation;Texture;Fuzzy set;Foreground;Background

期刊名称：OPTIK （ 影响因子：2.443； 五年影响因子：1.955 ）

ISSN： 0030-4026

年卷期： 2015 年 126 卷 24 期

页码：

收录情况： SCI

摘要： Target objects are direct characteristics of image description, but there are significant limitations, including the image being sensitive to changes in global illumination, etc., which lead to lack direct descriptive ability for objects in an image. Image target segmentation is one of the primary image processing operations, which means it is the first operation of the processing of an image. For the segmentation of a target area from the image, there are two kinds of existing methods. One method is to manually remove the obstructions to be a uniform color fill or outline its contours; and another way is to use the shortest path algorithm or the expansion of biology technique to extract optimal edges. For an image with unclear target boundaries and background, it is very necessary to eliminate the interfering information by transforming the interference information into fuzzy sets. In this paper, to solve the complex background images and the image target segmentation error, considering the dominance on image processing of fuzzy sets, the maximum fuzzy correlation criterion is proposed. Image is converted to a fuzzy domain, and then the maximum fuzzy correlation criterion is calculated. It is important to optimize the image maximum fuzzy membership function. Finally, experiment on leaf and fruit agricultural images, the results show that more edge details can be detected by fuzzy sets. (C) 2015 Elsevier GmbH. All rights reserved.

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