文章基本信息

标题：A hybrid approach for categorizing images based on complex networks and neural networks
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作者：Ali Ebrahimi ; Kamal Mirzaie ; Ali Mohamad Latif 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：2
页码：1795-1806
DOI：10.11591/ijece.v12i2.pp1795-1806
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：There are several methods for categorizing images, the most of which are statistical, geometric, model-based and structural methods. In this paper, a new method for describing images based on complex network models is presented. Each image contains a number of key points that can be identified through standard edge detection algorithms. To understand each image better, we can use these points to create a graph of the image. In order to facilitate the use of graphs, generated graphs are created in the form of a complex network of small-worlds. Complex grid features such as topological and dynamic features can be used to display image-related features. After generating this information, it normalizes them and uses them as suitable features for categorizing images. For this purpose, the generated information is given to the neural network. Based on these features and the use of neural networks, comparisons between new images are performed. The results of the article show that this method has a good performance in identifying similarities and finally categorizing them.
关键词：complex network;key points;network similarity;neural network;small-world network