DataCrop: A Generic Tool for Crop Data Set Generation

Integration between Quality Control and Industry 4.0 was explored seeking to obtain the best quality of the final product. This project aims to create an algorithm that creates a large data set that will train the Machine Learning model to achieve Automated Quality Control in Industry 4.0. The Methodology applied started with Data Acquisition by capturing a video of the fruits on the conveyor, afterwards applying Video Processing by cutting this video into frames to obtain raw data, then applying Image Processing on the raw data to clean it using Color Detection and Contour and Size Detection approaches, these methods resulted in the creation of two datasets of fresh and rotten oranges, with a total of 1700+ images of oranges. This paper presents the collection of a large dataset in addition to cleaning this data and make it ready for training and testing, Also to create an algorithm that creates large datasets of crops automatically