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In this work, a combination of artificial neural network (ANN), Fourier descriptors (FD) and spatial domain analysis (SDA) has been proposed for the development of an automatic fruits identification and sorting system. Fruits images are captured using digital camera inclined at different angles to the horizontal. Segmentation is used for the classification of the preprocessed images into two non-overlapping...
In order to improve the citrus grading accuracy, fractal dimensions which characterize the color and shape features of citrus fruit were analyzed. Samples were from Citrus unshiu Marc.cv.unbergii Nakai. For each sample, images from peduncle, calyx and two opposite sides were collected. These four images were cut, removed backgrounds, and converted from RGB space to HSI one, then by the following methods,...
In this paper, we adopt BP neural network as classification method and established the emotion model to simulate people's emotion based on image template. For achieving this purpose, firstly, we used 9 images which has different features of the famous psychologist Furnham's Shape & Color Test as templates and the basis of emotion classification. Then, we got a vector which has 27 dimensions by...
The new automatic classification devices for products based on machine vision techniques value the shape and color parameters so as to suitably assess the latter. These parameters may also be turned to good account by the machine vision techniques that proved to be applicable in several domains. One can especially apply these techniques in the inspection and analysis systems of industrial products...
In this paper, we propose a real-time forest fire detection algorithm using artificial neural networks based on dynamic characteristics of fire regions segmented from video images. Fire region is obtained from image with the help of threshold values in HSV color space. Area, roundness and contour are computed for fire regions from each 5 continuous frames. The average and mean square deviation of...
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