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Detection of green apples in natural scenes based on saliency theory and Gaussian curve fitting

International Journal of Agricultural and Biological Engineering 2018年第1期11卷 192-198页

作者： Bairong Li Yan Long Huaibo Song College of Mechanical and Electronic Engineering Northwest A&F UniversityYangling 712100ShaanxiChina Key Laboratory of Agricultural Internet of Things Ministry of AgricultureYangling 712100ShaanxiChina Key Laboratory of Agricultural Information Perception and Intelligent Services Yangling 712100ShaanxiChina

green apple targets are difficult to identify for having similar color with backgrounds such as *** primary goal of this study was to detect green apples in natural scenes by applying saliency detection and Gaussian curve fitting ***,the image was represented as a close-loop graph with superpixels as *** nodes were ranked based on the similarity to background and foreground queries to generate the final saliency ***,Gaussian curve fitting was carried out to fit the V-component in YUV color space in salient areas,and a threshold was selected to binarize the *** verify the validity of the proposed algorithm,55 images were selected and compared with the common used image segmentation algorithms such as k-means clustering algorithm and FCM(Fuzzy C-means clustering algorithm).Four parameters including recognition ratio,FPR(false positive rate),FNR(false negative rate)and FDR(false detection rate)were used to evaluate the results,which were 91.84%,1.36%,8.16%and 4.22%,*** results indicated that it was effective and feasible to apply this method to the detection of green apples in nature scenes.

关键词： image processing green apple natural scene machine vision object detection saliency theory Gaussian curve fitting

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