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Proceedings Paper

Determination of mango fruit from binary image using randomized Hough transform
Author(s): Mohamed Rizon; Nurul Ain Najihah Yusri; Mohd Fadzil Abdul Kadir; Abd. Rasid bin Mamat; Azim Zaliha Abd Aziz; Kutiba Nanaa
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Paper Abstract

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.

Paper Details

Date Published: 8 December 2015
PDF: 5 pages
Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 987503 (8 December 2015); doi: 10.1117/12.2228511
Show Author Affiliations
Mohamed Rizon, Univ. Sultan Zainal Abidin (Malaysia)
Nurul Ain Najihah Yusri, Univ. Sultan Zainal Abidin (Malaysia)
Mohd Fadzil Abdul Kadir, Univ. Sultan Zainal Abidin (Malaysia)
Abd. Rasid bin Mamat, Univ. Sultan Zainal Abidin (Malaysia)
Azim Zaliha Abd Aziz, Univ. Sultan Zainal Abidin (Malaysia)
Kutiba Nanaa, Univ. Sultan Zainal Abidin (Malaysia)


Published in SPIE Proceedings Vol. 9875:
Eighth International Conference on Machine Vision (ICMV 2015)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev, Editor(s)

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