Determination of mango fruit from binary image using randomized Hough transform

• Main Authors: Mohd Rizon, Mohamed Juhari, Abd. Rasid, Mamat, Mohd Fadzil, Abdul Kadir, Azim Zaliha, Abd Aziz, Nurul Ain Najihah, Yusri, Nanaa, K
• Format: Conference or Workshop Item
• Language: English
• Published: 2015
• Subjects: S Agriculture (General); TJ Mechanical engineering and machinery
• Online Access: http://eprints.unisza.edu.my/551/1/FH03-FRIT-16-05453.jpg; http://eprints.unisza.edu.my/551/
• Institution: Universiti Sultan Zainal Abidin

A method of detecting mango fruit from RGB input image is proposed in this research. From the input image, the image is processed to obtain the binary image using the texture analysis and morphological operations (dilation and erosion). Later, the Randomized Hough Transform (RHT) method is used to find the best ellipse fits to each binary region. By using the texture analysis, the system can detect the mango fruit that is partially overlapped with each other and mango fruit that is partially occluded by the leaves. The combination of texture analysis and morphological operator can isolate the partially overlapped fruit and fruit that are partially occluded by leaves. The parameters derived from RHT method was used to calculate the center of the ellipse. The center of the ellipse acts as the gripping point for the fruit picking robot. As the results, the rate of detection was up to 95% for fruit that is partially overlapped and partially covered by leaves.