Fruit Recognition and Weight Scale Estimation Based on Visual Sensing - Budi Sugandi; Ria Wahyu; Sindi Apriliana; Fitri Ramadani Putri (International ABEC, 2022)
This paper aims to develop a system to recognize fruit and estimate its weight scale based on visual sensing. The images of fruit are captured by camera and processed by image processing to be recognized and estimated their weight. The fruit recognition is performed based on average of RGB histogram. The RGB histogram of each fruit is calculated and saved as training data. To evaluate the recognition process, the testing data is compared with training data. The weight scale estmation is performed by calculating the height dan width of the detected fruit image. The regression equation is used to determine the weight of the fruit. The experiment was performed to 8 types of fuit with 10 samples data of each. The experiment results show the effectivenes of the algorithm to recognize and estimate the weight of fuit with average error 9.38 % of recognition and 4.85% of weight estimation.