Detecting Mango Fruits by using Randomized Hough Transform and Backpropagation Neural Network

Nanaa, Kutiba and Mohamed Juhari, Mohd Rizon and Abd Rahman, Mohd Nordin and Ibrahim, Yahaya and Abdul Aziz, Azim Zaliha (2014) Detecting Mango Fruits by using Randomized Hough Transform and Backpropagation Neural Network. In: International Conference on Information Visualisation (IV) (2014), 16-18 July 2014, Paris, France.

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Abstract

A new method for mango detection is presented in this paper. This method is based on preprocessing operators on image which includes converting to gray image, finding edges, calculating distances to edges, opening morphology and converting to binary color image. To take advantage of oval shaped mango fruit, we apply Randomized Hough Transform method to detect potential places for mango fruit in input images. By using Backpropagation Neural Network, we recognize mango fruits from these potential places. The dataset used to implementing this paper is 50 RGB images captured of mango fruits on trees. As shown in experimental results, in the case of clear fruit in input images, the detection rates up to 96.26% while it decreases in the case of partially covering or overlapping. However, this method can be applied to detect other fruits in varied sizes and colors.

Item Type: Conference or Workshop Item (Paper)
Keywords: Detecting Mango, image recognition, feature extraction, image segmentation, neural network, watershed algorithm, Randomized Hough Transform, detecting Fruits
Subjects: N Fine Arts > N Visual arts (General) For photography, see TR
Faculty / Institute: Faculty of Applied Social Sciences
Depositing User: Prof Datuk Yahaya Ibrahim
Date Deposited: 18 Dec 2014 07:44
Last Modified: 10 Mar 2015 05:16
URI: http://erep.unisza.edu.my/id/eprint/2031

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