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Content Based Image Retrival has wide application in the field of communication via internet. There exists various methods for retriving an image from the vast set of data present in the desktop, laptop, workstations and internet. The proposed Histogram positional centroid for image retrival technique uses histogrm feature extraction and position centroid. The Histogram Positional Centroid for Image...
As an important visual characteristic, color has been widely applied in content based image retrieval. The paper adopted the RGB color model, wherein intersection distance method, Euclidean distance method and correlation distance method based on color histogram characteristics were applied respectively in the experiments of the same sample image and the same image database. Experimental results show...
Under the environment of big data, retrieval becomes a crucial technology and image retrieval is paid more attention and widely used. The paper proposes a second-order retrieval algorithm, of which can be used to retrieval the similar images. Firstly, extracting image sift features. Then, build frequency table of characteristic words by k-means clustering and bag of word algorithm. Finally, based...
The problems of accuracy and computational complexity in extracting image features(color, texture and shape) in traditional Image retrieval algorithm result in a bigger error of image retrieval result and the lower efficiency of retrieval. A Content-Based Multi-Feature Comprehensively Weighting Video-Image Retrieval Algorithm is proposed to settle the problem. The essence of the algorithm is, set...
With the rapid growth of image database, content-based image retrieval (CBIR) technology with its high value in theory and application has become a hot topic in the field of image processing. A retrieval method which combines color and texture feature is proposed in this paper. According to the characteristic of the image texture, we can represent the information of texture by fusion algorithm combines...
Content based image retrieval techniques have been studied extensively in the past years due to the exponential growth of digital image information available in recent years with the widespread use of internet and declining cost of storage devices. Many techniques such as relevance feedback, multi query systems, etc. have been employed in CBIR systems to bridge the semantic gap between the low level...
This paper presents a study on the effectiveness of hierarchical clustering techniques application and classification for imaging context in the Content-Based Image Retrieval (CBIR). The study has the purpose to compare the obtained results from using different hierarchical clustering algorithms with various input parameters and configurations using two types of comparison techniques. The aims is...
To further enhance the efficiency of color histogram - based image retrieval algorithm, this paper presents a new algorithm which looks for maximum color lump, extracts its local histogram, and integrates with the original histogram. The algorithm adds spatial distribution characteristics of color while retaining the original algorithm, thus reduci ng absolute dependence on the color for retrieval...
Colorizing of grayscale images is a frequent and a widely used phenomenon in image processing. The approach presented in the paper is an automated one, consisting of a pair of sequential steps; reference image selection from the database followed by pixel coloring using luminance and neighbourhood statistics matching algorithm. The efficiency of the proposed technique is highlighted by the use of...
Memetic Algorithm (MA) is a meta-heuristic algorithm which combines an Evolutionary Algorithm (EA) and a local search algorithm. In this work, we design a cooperate memetic algorithm (CMA) for image retrieval. We propose a novel image indexing method based on YCbCr color space and 4096-tree. And then we describe the memetic algorithm with local search chain and cooperate memetic algorithm (MA-LSCH-CMA)...
Image retrieval methods based on the Scale Invariant Feature Transform (SIFT) algorithm have good performance except for the characteristics of time-consuming and high dimension feature vectors. This paper realizes an improved image retrieval method combining saliency maps with SIFT. The saliency map algorithm is used to define and detect the visually salient image regions which will be used in feature...
Because of the fast developing technologies in multimedia devices, we are able to receive huge amounts of images from daily life. Once these images have been stored, the next step is to figure out how to retrieve the desired pictures quickly and accurately from the database. In this paper, we intend to develop an efficient image retrieval algorithm. Using this algorithm, we can retrieve desired images...
In order to not only improve the storage efficiency, retrieval speed and accuracy of the existing content-based image retrieval algorithm, but also improve the quality of user experience, this paper proposes a novel improved algorithm about content-based image retrieval oriented by users' experience. According to the three elements of human visual color characteristics, this algorithm firstly quantifies...
A new color-based image retrieval method is proposed in the paper. The quantization precision of this algorithm is higher than that of supervised method and its efficiency well than unsupervised way. First, through the distance-matrix of color, the sample image is clustered in a self-organizing way, thus its palette can be obtained. Based on the palette, other images in the database are mapped in...
Study the global histogram algorithm and the rigid block algorithm in image retrieval, in order to improve the lack of spatial information in the global histogram, and to improve the lack of rotation invariance and image integrity in the rigid block, this paper proposed block weighting — the color feature algorithm. The algorithm first conduct color image a rigid segmentation, then sort the second...
With the rapid development of the information age and the wide range of use of multimedia technology, the problem how to solve a large number of efficient management of multimedia information has become an urgent need. In this paper, improvement ideas of the algorithm by analyzing the principle of traditional texture roughness retrieval algorithm is summarized and realized, and improved texture roughness...
Localizing an object in an image is a common task in the field of computer vision, and correlograms are often used for content-based image retrieval. This paper proposes an efficient object localization algorithm for query-by-sub region. The new algorithm utilizes correlogram back-projection in the chromaticity coordinates to handle the problem of sub-region querying. This approach enables users to...
Content Based Image Retrieval (CBIR) mainly contains two phases: first, to represent an image; second, to measure the dissimilarity between two images. Expectation-Maximization (EM) is a popular algorithm for clustering Gauss mixtures for the image representation, but the greedy nature of EM make it hard to get an optimal model for CBIR. In this paper, we introduce an improved EM algorithm for clustering...
Facing a great mass of clothing images on the Internet and the improvement of image retrieval result, text-based image retrieval has not perfectly meet the needs of people. Content-based retrieval increasingly shows its powerful search capabilities. But its problems, such as semantic gap and precise search, have not been resolved very well. Image for the clothing, this paper put forward that using...
This study proposes an algorithm where edge shape information is retrieved using a vote based rearranged chain code. The proposed algorithm rearranges and normalizes the chain code of edges to create a maximum vote based normalization chain code whose correlativity is reinforced. As it obtains cyclical maximum values from the chain code, rearranges them and flips code values according to the frequency,...
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