Nowadays computer vision systems are widely used for identification, classification and grading of different kind of fruits. Existing research concentrates on features like size of the fruit, colour, shape and texture for classification and maturity detection of mango fruits. Colour of the fruit is one of the prominent feature, though a lot of effort is focused towards identification, maturity and defect detection of mango using colour features,less attempts are made in the direction of the identification of artificially ripening of mango fruits.From another perspective very few attempts are concentrated towards deeper analysis of colour features of the fruits. In order to solve these issues this research paper proposes a new framework for detection of artificial ripening of mango fruit based on MPEG-7 colour descriptors. The proposed scheme includes three stages: first, a pre-processing stage consisting of masking, filtering, segmenting and cropping of an image followed by dominant colour extraction using dominant colour descriptors which are finally mapped with the help of clustering to identify the artificial ripening of mango fruit. The results of experimentsis carried out on two different datasets involving four types of mangoes which demonstrates robustness and efficiency of the proposed method against various other methods.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org