خوشه بندي خودكار با استفاده از الگوريتمهاي فرا ابتكاري به منظور بازيابي مبتني بر محتواي تصاوير ديجيتال

Automatic Clustering Using Metaheuristic Algorithms for Content Based Image Retrieval

Development of internet networks and mobile phone tools with image capturing capabilities and network connectivity within the recent years have led to defining new services and applications , using such tools. In this article, automatic clustering method using evolutionary and metaheuristic algorithms used in order to identify and categorize various kinds of digital images. For this purpose, a database of images prepared, and then k-means clustering method using evolutionary algorithms and optimization applied on these images. The results of retrieval indicate that automatic clustering using particle swarm optimization (PSO) algorithm has higher average retrieval accuracy in comparison with other methods.

Development of internet networks and mobile phone tools with image capturing capabilities and network connectivity within the recent years have led to defining new services and applications , using such tools. In this article, automatic clustering method using evolutionary and metaheuristic algorithms used in order to identify and categorize various kinds of digital images. For this purpose, a database of images prepared, and then k-means clustering method using evolutionary algorithms and optimization applied on these images. The results of retrieval indicate that automatic clustering using particle swarm optimization (PSO) algorithm has higher average retrieval accuracy in comparison with other methods.