Graph segmentation is promising as a very effective process for learning the complex structures and relationships hidden in disease data. Segmentation of citrus fruit diseases is a major task of image processing. There is no common segmentation process that can deal with all diseased portions, and the correct solution will always to a certain degree depend on subjectivity. To solve these issues, in this paper to develop a novel Graph based RecuroMatch (GRM) segmentation algorithm to discover citrus fruit diseases with different illumination conditions. To identify the diseased regions in citrus fruit, the GRM algorithm has to be described. The proposed work of a citrus fruit segmentation process presents three tasks namely, i) Image pre-processing: it is carried out using remove the irrelevant noises; ii) Citrus fruit features extraction: Feature extraction using new Colpromatix color space model, Size, Texture, Shape, and Coarseness; and iii) Graph based RecuroMatch segmentation process is an important process to discover the disease feature of an image. Segmentation process is playing an important function in systems for disease portion recognition, extracting, and examination.