A Modified Canny Edge Detection Algorithm for Fruit Detection & Classification

This study presents an image processing procedure to identify two different classes and types of fruits. The proposed method recognizes fruits by extracting two features (color and shape) based upon the training dataset analysis. In this study, an image processing method has been done using Canny Edge Detection (CED) algorithm to identify and sort the fruits. In addition to that modified Canny Edge Detection (MCED) algorithm is proposed to develop a fruit recognition method using color and shape of the fruits. In this work, only two different types of fruits (i.e. apples and oranges) are chosen for the experiment. At the end of this study, a comparative study has been shown to evaluate the performance of CED algorithm and MCED algorithm based on the training dataset.

[1]  E.E. Pissaloux,et al.  Image Processing , 1994, Proceedings. Second Euromicro Workshop on Parallel and Distributed Processing.

[2]  AMRUTA L KABADE,et al.  Canny edge detection algorithm , 2016 .

[3]  Tao Sun,et al.  An Improved Canny Edge Detection Algorithm , 2013, 2014 IEEE International Conference on Mechatronics and Automation.

[4]  Beant Kaur,et al.  Mathematical morphological edge detection for remote sensing images , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[5]  M. P. Dale,et al.  Determination of ripeness and grading of tomato using image analysis on Raspberry Pi , 2015, 2015 Communication, Control and Intelligent Systems (CCIS).

[6]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.