In this paper, we present a new and effective color image retrieval scheme for combining all the three i.e. color, texture and shape information, which achieved higher retrieval efficiency. Firstly, the image is predetermined by using fast color quantization algorithm with clusters merging, and then a small number of dominant colors and their percentages can be obtained. Secondly, the spatial t...

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...

The failure of simple constituent-quark models' to explain' the new experimental values of X and magnetic moments ' contrasts sharply with the remarkable success of the naive constituent-quark model in describing the nucleon and A magnetic moments"" and the hadron mass spectrum. " " The underlying dynamical reasons for this success are not understood and it all may be accidental, ' However, the...

In this paper we propose to introduce a new color interactive and selective filtering tool based on the minimization of a weighted vectorial total variation term TVg with the L2 norm as data term. Our goal is to filter one region of an image while preserving the other using a minimal interaction with the user. To this end, we take benefit of a weighted vectorial regularization term TVg based on...

In this paper we propose a new descriptor for birds search. First, our work was carried on the choice of a descriptor. This choice is usually driven by the application requirements such as robustness to noise, stability with respect to bias, the invariance to geometrical transformations or tolerance to occlusions. In this context, we introduce a descriptor which combines the shape and color des...

For TRECVID 2008 concept detection task, we principally focus on: (1) Early fusion of texture, edge and color features TECM, abbreviation of the combined TF*IDF weights based on SIFT features, Edge Histogram, and Color Moments. (2) To improve the training efficiency and explore the knowledge between concepts or hidden sub-domains more easily and efficiently, we propose a novel method based on L...

Accurately and automatically detecting image orientation is a task of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on these features: color moments; harris corner; phase symmetry; edge direction histogram. The statistical learning support vector machines, AdaBoost, Subspace classifier are used in our approach ...

New invariant features are presented that can be used for the recognition of planar color patterns such as labels , logos, signs, pictograms, etc., irrespective of the viewpoint or the illumination conditions, and without the need for error prone contour extraction. The new features are based on moments of powers of the intensities in the individual color bands and combinations thereof. These m...

A novel approach of Content Based Image Retrieval(CBIR), which combines color, texture and shape descriptors to represent the features of the image, is discussed in this paper. The proposed scheme is based on three noticeable algorithms: color distribution entropy(CDE), color level co-occurrence(CLCM) and invariant moments. CDE takes the correlation of the color spatial distribution in an image...

Retrieval of an image is a more effective and efficient for managing extensive image database. Content Based Image Retrieval (CBIR) is a one of the image retrieval technique which uses user visual features of an image such as color, shape, and texture features etc. It permits the end user to give a query image in order to retrieve the stored images in database according to their similarity to t...