Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...

with quick development of digital images and the availability of imaging tools, massive amounts of images are created. therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. automatic image annotation (aia) or refers to attaching words, keywords or comments to an image or to a selected part of it. in this paper,...

in this paper we propose novel algorithms for retrieving dental images from databases by their contents. based on special information of dental images, for better content based dental image retrieval and representation, the image attributes are used. we propose disr (dental image segmentation and retrieval), a content-based image retrieval method which is robust to translation and scaling of th...

introduction: content based image retrieval (cbir) is a method of image searching and retrieval in a  database. in medical applications, cbir is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. as the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retri...

In this article, a fabulous method for database retrieval is proposed.  The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shap...

Image retrieval is an important research field which has received great attention in the last decades. In this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. For text-based features, keywords and for content-based features, color and texture features have been used. Query in this system contains some keywords and an input...