Content Based Image Retrieval Components; Color, Shape and Texture

Santosh Bharti ,  Prof.Lalit Wadhwa

Padmashree  Dr. D. Y. Patil Institute of Engineering   and Technology, Pimpri, Pune – 411 018


 Recently, digital content has become a significant and inevitable asset for any enterprise and the need for visual content management is on the rise as well. There should be an increase in attention towards the automatic management and retrieval of digital images because of   the drastic development in the number and size of image databases. Content-based image retrieval (CBIR), as we see it today, is any technology that in principle helps organize digital picture archives by their visual content. The increased need of content based image retrieval technique can be found in a number of different domains The such as Agriculture, Data Mining, Research laboratories, Medical Field, Crime Prevention, Weather department , and Management of Earth Resources. Image retrieval based on different components has strong research scope. In this paper we present some technical details about the components used for the retrieval of images and algorithm are also defined for retrieval of images by using the components i.e. color, texture and shape information, and achieve higher retrieval efficiency using dominant color feature.



CBIR, Retrieval, color, texture, shape


From times the images have been the mode of communication for human being. Now a days, we are able to generate, store, send and share large amount of data because of the growth of Information and Communication Technology. Due to exponential increase of the size of the so-called multimedia files in recent years because of the substantial increase of affordable memory storage on one hand and the wide spread of the World Wide Web (www) on the other hand therefore, fast retrieval of images from large databases is an important problem that needs to be addressed. High retrieval efficiency and less computational complexity are the desired characteristics of CBIR systems. A large collection of images is referred to as image database. An image database is a system where image data are integrated and stored. In conventional image databases, images are text-annotated and image retrieval is based on keyword searching. Some of the disadvantages of this approach are:

1. Keyword based image retrieval is not appropriate because there is no fixed set of words that describes the image content;

2. keyword annotation is very subjective. To overcome the above disadvantages in text-based retrieval system, content based image retrieval (CBIR) was introduced in the early 1980s. In CBIR, images are indexed by their visual content, such as color, texture, shapes. From historical perspective, probably the first use of CBIR goes back to D. Kato in early nineties where he implemented what sounds to be the first automated image retrieval system using color and shape features. This motivated the intensive research carried out in many aspects of CBIR.

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Volume -01, Issue -05 , December 2013.

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