EXTRACTION OF SHAPE AND TEXTURE STATISTICAL ON THE DIGITAL IMAGE PAYO KERINCI

Ekstraksi Ciri, Bentuk, Tekstur Statistis, Citra Digital, Gray Level Co-oocurence Matrix

Abstract

Payo Kerinci rice is one of the regional superior products. There are several types of payo kerinci rice such as squirrel, guava, support, and cross tailed payo rice. Feature extraction is a stage in extracting features / information from objects in an image that you want to distinguish from other objects. This research uses form and texture feature extraction method based on statistical gray level co-occurrence matrix. The image shape and texture feature extraction uses parameter values metric, eccentricity, contrast, correlation, energy, and homogeinity by determining the characteristics based on broad values, circumference of the object, and the shape of the image with distance (d) = 1, with the direction 0⁰, 45⁰, 90⁰ and 135⁰. The research data consisted of 24 images, 6 images of squirrel tails, 6 guava images, 6 supported images, and 6 cross images. The system created can determine image characteristics based on statistical form and texture.