Abstract
Digital image collection as rapidly increased along with the development of computer network. Image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and color similarity. Retrieving images based on the content which is color, texture, and shape is called content based image retrieval (CBIR). The content is actually the feature of an image and these features are extracted and used as the basis for a similarity check between images. The algorithms used to calculate the similarity between extracted features. There are two kinds of content based image retrieval which are general image retrieval and application specific image retrieval. For the general image retrieval, the goal of the query is to obtain images with the same object as the query. Such CBIR imitates web search engines for images rather than for text. For application specific, the purpose tries to match a query image to a collection of images of a specific type such as fingerprints image and x-ray. In this paper, the general architecture, various functional components, and techniques of CBIR system are discussed. CBIR techniques discussed in this paper are categorized as CBIR using color, CBIR using texture, and CBIR using shape features. This paper also describe about the comparison study about color features, texture features, shape features, and combined features (hybrid techniques) in terms of several parameters. The parameters are precision, recall and response time.
Highlights
With the widespread use of computer network, collection of information data such as image has quickly grown and continues to increase in the future
Retrieving images based on the content which is color, texture, and shape is called content based image retrieval (CBIR)
CBIR techniques discussed in this paper are categorized as CBIR using color, CBIR using texture, and CBIR using shape features
Summary
With the widespread use of computer network, collection of information data such as image has quickly grown and continues to increase in the future. Due to rapidly grown of internet, every image information and data was collected and digitized. In order to access this huge amount of data, efficient technique and method is needed for querying the indexed image database. Content Based Image Retrieval (CBIR) system was introduced in 1990 [1] It is basically a techniques used for automatic retrieval of images in a large database that perfectly matches the query image. For the general image retrieval, the goal of the query is to obtain images with the same object as the query Such CBIR imitates web search engines for images rather than for text. The need for efficient finding, searching and retrieval of digital image has been rapidly increase in many image processing application, viz, medicine, commerce, crime prevention, military, education, culture, and entertainment [2]
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