Ripe tomato detection and grading system using image processing techniques

Fadzli, Mohammad Firdaus (2020) Ripe tomato detection and grading system using image processing techniques. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Nowadays the food quality grading and classification is become a big issue in agriculture. It is difficult and consume too much time to manually find the best food quality by people in the market. Insufficient maturity of the fruit is the main problem too. For this proposed system, a tomato is used as the product to be tested for food quality. Therefore, it is necessary to recognize the appropriate pattern to determine the ripeness of the fruit. One of the recognition patterns of tomatoes image is by using color detection algorithm. This paper explained the technique for the automatic detection of skin surfaces of tomatoes in digital color images and determine the size of tomato based on the binary image. The system describes a two-step process, the first of which detects regions that are likely to contain tomato skin in color images, and then extracts information from these regions that might indicate the location of the tomato in the image. The image that has been processes must use in percentages value of color in order to classify the ripeness of tomatoes. The size of tomato image will be determined to get a grade of tomato. MATLAB software and its image processing toolbox is used in images processing and analysis. A Graphical User Interface (GUI) for ripeness tomato detection and grading system by using MATLAB R2020b is developed. For future recommendation, this system can be upgraded by adding other types of vegetables and fruits

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