A New Algorithm for Greenhouse Corridor Edge Detection with RGB-D Data

文献类型： 外文期刊

第一作者： Qiu Quan

作者： Qiu Quan;Meng Zhijun;Qiu Quan;Meng Zhijun

作者机构：

关键词： RGB-D;greenhouse corridor detection;dominant color;connected region;canny

期刊名称：2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

ISSN： 2379-7711

年卷期： 2015 年

页码：

收录情况： SCI

摘要： This paper presents a new algorithm of corridor edge detection in greenhouse scenes with RGB-D sensor. The algorithm tries to tackle the detection problem considering corridor's 3 features, including 3D position, dominant color and binary edges. Firstly, a height interval will be used to collect 3D points for generating a corridor candidate set. Secondly, dominant color abstracting will help to delete outliers with similar height but different colors. And connected region labeling will help to get rid of outliers with similar height and color but different locations. After that dominant color abstracting and connected region labeling will be repeated on the whole image set, and the resulted region will have different edges from the one generated from corridor candidate set. Then the common edges will be taken as root edges. Thirdly, a directional growth strategy will finally mark out the whole corridor edges on canny edges map, with root edges as its start. Experiments are carried out on real RGB-D data collected in greenhouse, and the effectiveness of the new algorithm is verified.

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[1]Selecting Candidate Regions of Clustered Tomato Fruits Under Complex Greenhouse Scenes Using RGB-D Data. Qiu Quan,Qiao Xiaojun,Jiang Kai,Feng Qingchun,Tian Lanlan. 2017

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