An Effective CBIR using Texture
نویسندگان
چکیده
Content Based Image Retrieval is one of the active research areas. With emerging technologies of multimedia ,communication and processing large volume of image database is used . Current approaches include the use of color, texture and shape information for CBIR. Texture feature is a kind of visual characteristic that does not rely on color and intensity and reflects the intrinsic phenomenon of images. It is total of all intrinsic surface properties. This enforces use of texture widely for image retrieval. Texture may consists of some basic primitives and may also describe the structural arrangement of a region and the relationship of the surrounding regions. Our approach uses the statistical feature using Gray Level Co-occurrence Matrix. For the texture based image retrieval Gray Level Co-occurrence Matrix can be used. A one to one matching scheme is used to compare the query and target image. Experimental results demonstrate that the propose method is very efficient and superior to some other existing method. General Terms Computer Vision, Image Processing, Pattern Recognition, .
منابع مشابه
Content Based Image Retrieval by Multi Features using Image Blocks
Content based image retrieval (CBIR) is an effective method of retrieving images from large image resources. CBIR is a technique in which images are indexed by extracting their low level features like, color, texture, shape, and spatial location, etc. Effective and efficient feature extraction mechanisms are required to improve existing CBIR performance. This paper presents a novel approach of ...
متن کاملHybrid Feature of Tamura Texture Based Image Retrieval System
Storage and retrieval of images in such libraries has become a real demand in industrial, medical, and other applications. Content-based image indexing and retrieval (CBIR) is considered as a solution. In such systems, in the indexing algorithm, some features are extracted from every picture and stored as an index vector. We apply tamura texture features on digital images and compute the low or...
متن کاملContent Based Image Retrieval Using Gabor Texture Feature and Color Histogram
In this paper, we present content based image retrieval using two features color and texture. Humans tend to differentiate images based on color, therefore color features are mostly used in CBIR. Color histogram is mostly used to represent color features but it cannot entirely characterize the image. Color Histogram is also rotation invariant about the view axis. Regularity, directionality, smo...
متن کاملA New Content Based Image Retrieval Method Using Contourlet Transform
One of the challenging issues in managing the existing large digital image libraries and databases is Content Based Image Retrieval (CBIR). The accuracy of image retrieval methods in CBIR is subject to effective extraction of image features such as color, texture, and shape. In this paper, we propose a new image retrieval method using contourlet transform coefficients to index texture of the im...
متن کاملContent Based Image Retrieval Using Integration of Color and Texture Features
1451 ISSN: 2278 – 1323 All Rights Reserved © 2014 IJARCET Abstract— CBIR is a process of retrieve and display relevant images from large collection of image database on the basis of their visual content. CBIR is used for retrieval of images depending upon visual contents of images known as features. This paper focuses on color and texture based techniques for achieving efficient and effective r...
متن کاملIntegration of Color and Texture Features in CBIR System
Nowadays, rapid and effective searching for relevant images in large image databases has become an area of wide interest in many applications. The current image retrieval system is based on text-based approaches. This system has many challenges such as it cannot retrieve images that are context sensitive and the amount of effort required to manually annotate every image, as well as the differen...
متن کامل