CANNED PINEAPPLE GRADING USING PIXEL COLOUR EXTRACTION

Malaysia is a one of the main producer of canned pineapple in the world. According to Malaysian Pineapple Board Industry, it is about 5% of total production of canned pineapple is meant for export. MPIB was responsible in controlling the quality of product before exporting abroad. Quality inspection of the pineapple was done manually by quality inspector. The grade is depending on the color of the pineapple and producers need to get certification of grade before they can export to overseas. In this paper, we presented our study on automatic detection of canned pineapple grade using image processing technique. MPIB currently has done the quality inspection using expertise worker which is currently not suitable to be applied. This research develops to differentiate and classify the standard 15 and standard 16 of canned pineapple. The image data collections were controlled in order to avoid any outside lighting source. Then, Otsu’s method, morphological operation has been applied on the image to make sure the region of interest (ROI) quality is the best before multiplying it with original image. Using Red Green Blue (RGB), Hue Saturation Value (HSV) and CieLAB colour space the pixel colour were extracted using mean and standard deviation. 100% classification between two standard of canned pineapple was determined using Hue component in HSV colour space.

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