Inspection of Mango with Machine Vision Technique


  • Nursabililah Mohd Ali Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka, Malaysia
  • Nur Rafiqah Abdul Razif Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka, Malaysia
  • Mohd Safirin Karis Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka, Malaysia
  • Oh Kok Ken Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka, Malaysia
  • Wira Hidayat Mohd Saad Fakulti Kejuruteraan Elektronik & Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia
  • Amar Faiz Zainal Abidin Fakulti Kejuruteraan Elektrik, Universiti Teknologi Mara, Pasir Gudang, Johor, Malaysia


Colour Detection, Growth Rate, Mango's Quality, Shape Detection,


The entire project deals with development of colour detection and shape identification algorithm to detect and count the total number of mango on its tree with a camera and related MATLAB toolboxes. The conventional method in harvesting mango has its limitation which leads to the degradation of mango’s quality. Besides, the rate of production and the structure of the tree will be affected too. Nonetheless, the usage of algorithm of image processing could be employed for a better and precise mango’s farming. It differentiates the number of ripe and unripe mango based on the images captured and thus forecast the growth rate of the mango tree. Improving the rate of production as well as quality of the harvested mango are the main advantages. In short, it provides a quick review for the mango grower, agricultural developer and investor


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How to Cite

Mohd Ali, N., Abdul Razif, N. R., Karis, M. S., Kok Ken, O., Mohd Saad, W. H., & Zainal Abidin, A. F. (2016). Inspection of Mango with Machine Vision Technique. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(4), 25–29. Retrieved from

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