Discriminating Mature Tomatoes In Natural Outdoor Scenes By Computer Vision

The objective of this study was that mature tomatoes in natural outdoor scenes could be automatically discriminated from images by computer, and grounded for automatically picking fruits by robots .The main contents are:1. Proposing discriminating methods that discriminated the red color of the tomato based on color features in natural outdoor scenes and finding the tomato's centroid.Putting forward two classifying method under two color model , namely HIS discriminating method and RGB discriminating method ,based on studying and analyzing the color features of mature tomatoes , immature tomatoes and leaves in natural outdoor scenes . After processing tomatoes images , advancing a picking black body arithmetic which expunged a lot of small district which were wrongly discriminated for calculating the coordinate of the tomato's centroid by rule and line .Advancing a filling in inanition arithmetic for filling in inanition of district of tomatoes which was discriminated in especial circumstances . Making sure the exact address of the district of tomatoes which were discriminated . Putting forward a fixing on bound of the tomatoes' districts arithmetic for reducing bound of images , after processing , it offered a very advantaged condition for discriminating tomatoes more . Analyzing carefully some wrongly discriminating phenomena too.2. More discussing a discriminating project that discriminated the tomato's profile based on shape features.In order to extract shape features , images were processed by smoothing , wiping off noise , extracting confine , thinning , expunging small branches and filling a vacancy processes and so on . In this paper, median filter was used to smooth images. Advancing improved sobel arithmetic for extracting confine. Putting forward a Double linked List with two sides arithmetic for segmenting images . On the basis of analyzing shape features of tomatoes , leaves and branches ,we extract features of roundness , slightness , concavity degree and denseness depending on Fourier description . So we will found an appropriate classifying model to discriminate tomato's profile from images. Because color images in natural outdoor scenes was very difficult to be processed , this paper didn't put forward a concrete discriminating tomato's profile way based on shape features and only brought forward a discriminating project and did some basic studies for realizing to discriminate tomatoes based on shape features at last.