Title :
A new method for fruits recognition system
Author :
Seng, Woo Chaw ; Mirisaee, Seyed Hadi
Author_Institution :
Fac. of Comput. Sci. & Inf. Technol., Univ. of Malaya, Kuala Lumpur, Malaysia
Abstract :
Several fruit recognition techniques are developed based upon color and shape attributes. However, different fruit images may have similar or identical color and shape values. Hence, using color features and shape features analysis methods are still not robust and effective enough to identify and distinguish fruits images. A new fruit recognition system has been proposed, which combines three features analysis methods: color-based, shape-based and size-based in order to increase accuracy of recognition. The proposed method classifies and recognizes fruit images based on obtained feature values by using nearest neighbours classification. Consequently, our system shows the fruit name and a short description to user. The proposed fruit recognition system analysis classifies and identifies fruits successfully up to 90% accuracy. This system also serves as a useful tool in a variety of fields such as education, image retrieval and plantation science.
Keywords :
computer vision; feature extraction; image recognition; color features; computer vision; education; feature extraction; fruit images; fruits recognition system; image retrieval; nearest neighbours classification; plantation science; shape features; Classification algorithms; Computer science; Feature extraction; Image analysis; Image color analysis; Image recognition; Machine learning algorithms; Pattern recognition; Robustness; Shape; KNN classification; computer vision; feature extraction; fruit; recognition; shape;
Conference_Titel :
Electrical Engineering and Informatics, 2009. ICEEI '09. International Conference on
Conference_Location :
Selangor
Print_ISBN :
978-1-4244-4913-2
DOI :
10.1109/ICEEI.2009.5254804