CTDCIRS: Content based Image Retrieval System based on Dominant Color and Texture Features

Abstract

There is a great need of developing efficient content based image retrieval systems because of the availability of large image databases. A new image retrieval system CTDCIRS (color-texture and dominant color based image retrieval system) to retrieve the images using three features called dynamic dominant color (DDC), Motif co-occurrence matrix (MCM) and difference between pixels of scan pattern (DBPSP) is proposed. Initially the image is divided into eight coarse partitions using the fast color quantization algorithm and the eight dominant colors are obtained from eight partitions. Next the texture of the image is represented by the MCM and DBPSP. MCM is derived using a motif transformed image. MCM is similar to color co-occurrence matrix (CCM). MCM is the conventional pattern cooccurrence matrix that calculates the probability of the occurrence of same pixel color between each pixel and its adjacent ones in each image, and this probability is considered as the attribute of the image.MCM captures third order image statistics in the local neighborhood which describes the direction of textures but not the complexity of the textures. That is why the DBPSP is also considered as one of the texture features. The three features Dominant color, MCM and DBPSP are integrated to facilitate the image retrieval system. Experimental results show that the proposed image retrieval is more efficient in retrieving the user-interested images.

Content Based Image Retrieval Using Embedded Neural Networks with Bandletized Regions

“…These semantic classes are namely: Africa, Buses, Beach, Dinosaurs, Buildings, Elephants, Horses, Mountains, Flowers, and Food. The reason for our choice to report the result on these categories is that: these categories are the same semantic groups used by most of the researchers who are working in the domain of CBIR to report the effectiveness of their work [31,33,37,39,41], so a clear performance comparison is possible in term of the reported results. To further elaborate the performance of the proposed system, experiments are also performed on Columbia object image library (COIL) [33] having 7200 images from 100 different categories.…”

“…In this regard, the technique is compared with [31,33,37,39,41]. The reason for our choice to compare with these techniques is that these systems have reported their results on the common denomination of the ten semantic categories of Corel dataset as described earlier.…”

“…Dominant colors and edge orientations are then used for image representation purposes. In the work of [31] a color-texture and dominant color based image retrieval system (CTDCIRS) is proposed and three different features from the images, i.e., motif co-occurrence matrix (MCM), dynamic dominant color (DDC), and difference between pixels of scan pattern (DBPSP) are offered. In their first step, using a color quantization algorithm, the image is divided into an eight coarse partition and the dominant colors are obtained from every partition.…”

Combination of Local, Global and K-Mean using Wavelet Transform for Content Base Image Retrieval

“…The color and texture investigations are analyzed by means of two level grid frameworks and the shape distinction by Gradient Vector Flow. The comparison of investigation result of the proposed method with other system [16] [ 17] found that, the anticipated retrieval system gives better recital than the others [18]. Proposed CTDCIRS (color-texture and dominant color based image retrieval system), they employed collectively three of the features like Motif co-occurrence matrix (MCM), Difference between Pixels of Scan Pattern (DBPSP) which describes the texture features and Dynamic Dominant Color (DDC) to take out color feature for image retrieval.…”

Detecção de cenas em segmentos semanticamente complexos

“…Os descritores de cor apresentam os melhores resultados para a busca de imagens (Rao et al, 2011;Sandeep e Rajagopalan, 2002;Yang e Ahuja, 1998). O mais básico descritor de cor é o histograma de cores (Messing et al, 2001).…”