Labelled Image Dataset Preparation for Rice Seed Germination Prediction and Variety Classifictaion using Low Cost Devices - et. al., S. Durai, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Machine vision and Digital Image processing systems widely used in many of the applications like Quality control, Classification, Recognition, Identification, Security etc. For the implementation of machine vision system and machine learning, system must be feed by collection of images. Collecting the required images for the system are time consuming and complex task. We can collect the images from internet, research centres or existing data prepared by the researchers. Most of the systems images are not available, many of the researchers preparing the image datasets by themselves. Preparation of datasets needs costly equipments like high resolution cameras, highly configured computer systems, scanners etc. Nowadays handheld devices are equipped with high resolution cameras and cost also when compared to digital cameras very low. In this article we are going to demonstrate the step by step procedure of hardware setup, capturing image, processing images and feature extracted for those images by using mobile phone. For this implementation we have used Vivo z1pro mobile and prepared the data sets for the research of germination prediction and variety identification for the rice seeds. Preparing the datasets we have used four major rice seeds cultivated in Tamilnadu namely Andhraponni, Atchayaponni, KO50and IR20 which are collected from Agricultural university Trichirappalli,Tamilnadu,India. The prepared data set is freely available in https://github.com/duraitrichy/Riceseed.