DETECTION OF ARTIFICIALLY RIPENED FRUITS USING IMAGE PROCESSING

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DETECTION OF ARTIFICIALLY RIPENED FRUITS USING IMAGE PROCESSING

Abstract

In this paper, an efficient image processing technique is used to detect the artificially ripened bananas. Banana is an important fruit crop across the world. Nowadays to ripe the bananas, traders use many artificial methods (using chemicals). One of the artificial methods used is adding of calcium carbide. CaC2 contains the traces of arsenic and phosphorous which is the carcinogenic agent. The threshold based segmentation is used to segment the image from the bunch of bananas and some discriminatory features are extracted in frequency domain using Haar filter. Features are selected upto the third level of decomposition in wavelet domain and analysed fo discriminatory behaviour. The variation in the features of the images is related to the difference between artificially ripened and naturally ripened bananas. These statistical features are then analysed and used for identification of artificially ripened sample in these samples using support vector machine classifier. The experimental results indicate that the proposed method is efficient for identification of artificially ripened bananas.

Author

R. KARTHIKA K.V.M.RAGADEVI N.ASVINI

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International Journal of Advanced
Science and Engineering Research

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