Rinaldi
Image feature extraction done in image analysis based on the traditional pixel is not extracted effectively. This is due to the extraction that only represents the content. A very promising approach and the challenge are to extract a graph from an image that represents the content and their relationship. The results of graph extraction are obtained from the process of image segmentation. The selection of an appropriate segmentation method from many graph-based image segmentation methods is interesting to be reviewed. The method of super-pixel segmentation is one way to divide the image into regions. The regions obtained in segmentation are represented by vertices and edges represent connections between adjacent regions. This representation is called Region Adjacency Graph (RAG). In this study, graph extraction of “batik” images has been successfully performed where its representation uses RAG and segmentation uses the Minimum Spanning Tree method. The results of graph extraction have been tested in a simple image retrieval process using the VF2 graph matching method.
Penerapan Karya Tulis
Image feature extraction done in image analysis based on the traditional pixel is not extracted effectively.