Determination of the maturity state of huayco cream peach through image processing with Raspberry Pi

Abstract

The following study aims to develop an algorithm that allows determining the state of maturity of the Huayco-type cream peach, a Raspberry Pi 4 model B board, a Microsoft LifeCam HD-3000 webcam with USB connection, a micro-SD card was used and an adapter to view this information on the laptop, in addition the Python and OpenCV libraries were used. The model was previously trained to recognize and analyze images of peaches with open wounds, bruises, pressure marks, mold, among others. To calculate the overall brightness of each image, the RGB format was converted to grayscale and a formula was applied that determines the gray intensity value at each position, obtaining an accurate result. A code was created and executed that, when uploading the image and/or showing the Huayco peach live, shows us its percentage and the state of maturity in which it is, whether fresh, ripe or rotten, all done with Raspberry Pi 4 model B and the Linux operating system. It is concluded that the algorithm with Raspberry Pi and the Tensorflow and OpenCV tools were effective in determining the maturity status of the Huayco cream peach through image processing.