DETECCIÓN DE CENICILLA EN ROSA USANDO PROCESAMIENTO DE IMÁGENES POR COMPUTADORA

Abstract

Pests and diseases represent a problem in ornamental crops, which at the same time affect the international trade and therefore have to be controlled. The main markets for cut flowers are located in Europe, United States and Japan. Mexico is one of the main suppliers to USA. Roses are currently the most important ornamental crops and also they are very susceptible to diseases, which spread easily. It would be possible to conduct early protection and treatment applications if diseases could be detected on early stage as well as the causal agents. In this research a detection system of powdery mildew(Sphaerotheca pannosa)on rose was developed with Open CV. Open CV is an open source computer vision library, which is written in C and C++ language. The detection was made according to the HSV space color. The source image was converted from the RGB to the HSV space color and the disease and the plant parts were extracted according to the H, S and V information. After that the noise (white objects) was removed. Finally the accuracy of the detection was evaluated. The developed disease detection system is able to detect the powdery mildew disease through the HSV space color with Open CV. Better results were obtained when using close pictures (10 cm). The miss-matched rate caused mostly by halation when using distant pictures could be successfully avoided using active sensing which allows for disease detection even when using distant pictures.