PaLife: A Mobile Application for Palay (Rice) Health Condition Classification utilizing Image Processing and Pigment Analysis towards Sustainability of Palay Production

Agriculture industry is something on which the economy highly depends on. This is one of the reason why rice plant health condition detection, disease detection and pest detection plays an important role in the agricultural sector especially to the growers/farmers in order to administer and manage the farming of rice crops. This paper presents the development of a mobile application named PaLife for rice health condition classification utilizing image processing and pigment analysis. Local Binary Pattern Histogram, Convolutional Neural Network and Color Segmentation algorithms are implemented for the operation of automatic detection and provides accurate and reliable results and information for the users. The project is evaluated and tested using different scenarios and cases as well as the ISO 25010 software quality standard, which formed an over-all rating of Strongly Acceptable. The researchers found that the mobile application will highly assist the agricultural personnel on the administration and management of rice crops specially on rice health condition detection, disease detection, and pest detection. This mobile application may help a lot the agricultural sector in aiding their issues and needs through the use of reliable and accurate results and information.