Detecting mango fruits by using randomized hough transform and backpropagation neural network

Azim Zaliha, Abd Aziz and Mohd Nordin, Abdul Rahman and Mohd Rizon, Mohamed Juhari and Yahaya, Ibrahim (2014) Detecting mango fruits by using randomized hough transform and backpropagation neural network. In: 18yh ICIV, 18 September 2014, Paris.

Image FH03-FIK-15-02445.jpg Restricted to Registered users only Download (206kB)

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 Back propagation 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.

Actions (login required)

View Item