This code with regard to previous approaches, defined in both pixel- and object-based scenarios, presented a new hybrid method, based on the graph-based segmentation algorithm and Fractal net evolution approach (FNEA) which effectively and efficiently overcomes the mentioned problems. The proposed method, at the first stage, takes advantage of the high speed and reliable outcome of the graph-based segmentation method and then involves the capability of FNEA in merging the segments properly. Finally, it uses the well-known pixel-based classifiers in order to assign each segment into the right class label. When it comes to the assessment of the proposed method, we scrutinize the proposed method by comparing with pixel-based methods (KNN, SVM, and MLC) and Quad Tree as an object-based method.