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While much progress has been achieved in the field of content-based image retrieval (CBIR), almost all CBIR techniques operate on pixel data although virtually all images are stored in compressed form. In this invited paper, we present efficient and effective CBIR techniques that operate directly in the compressed domain and thus do not require full decompression for feature extraction. In particular,...
The numbers of digital images are increasing day by day and mining from large databases is becoming harder & harder. Indexing image data based on text is tiresome and error prone. If the indexing based on low-level feature of the image then it may reduce the workload and mining become faster. In this research paper we propose an indexing technique which indexes the digital images in the database...
High level image understanding and content extraction requires image regions analysis to reveal the spatial interaction between them. This paper aims to engender new attributes for scene description considering the relative position of the objects inside. A visual grammar of the scene is built using an extension for a Knowledge Based Image Information Mining system (KIM). The objects are extracted...
In the recent years, image retrieval is of high importance in the web community since there are so many useful images on web pages. Hence, it is a large challenge to make full use of so considerable data by conventional retrieval approach. The lack of semantic based retrieval capability has impeded application of remote sensing data. To address the issue, we propose a framework based on domain-dependent...
The homogeneous texture descriptor is one of MPEG-7 texture descriptors. This descriptor describes the texture information of an image or the region of interest in an image. A new texture feature wedge feature is proposed, which emphasizes the texture direction. The homogeneous texture descriptor owning the new feature is more suitable to content-based image retrieval system. The experimental results...
A novel image retrieval of JPEG image is proposed based on the statistical distribution and spatial information of the DCT coefficients. According to the distribution of the several AC coefficients, the AC distribution entropy is introduced. Furthermore, the effect of the spatial information of the AC coefficients on retrieval result is considered, a weight is introduced to improve the scheme. The...
An up-to-date comparison of state-of-the-art low-level color and texture feature extraction methods, for the purpose of content-based image retrieval (CBIR) is presented in this paper. The CBIR problem is motivated by the need to search the exponentially increasing space of image and video databases efficiently and effectively. We implement and compare color and texture feature extraction algorithms...
In content-based image retrieval, it is helpful to add a pre-classification module to classify a query image into attentive class or non-attentive class. Based on the pre-classification result, a suitable retrieval strategy is adopted for the query image presented. In this paper, we proposed a Multi-Layer Perceptron (MLP) classifier with the features extracted from saliency map to classify both the...
This paper presents an interface of image query system for content-based image retrieval.The proposed interface can split images into the regions and select an target region from the separated regions. We apply content-based image retrieval to the selected region as a query.The images in databases are also split into the areas in advance.The content features such as color and texture are extracted...
Content based image retrieval is a current research focus at home and abroad. With the increasing popularity of clothing e-commerce, the requirements of image based clothing retrieval are increasingly urgent. The clothing style is the essential characteristics. The paper presents the method of contour feature extraction, expression and matching to implement clothing image retrieval comprehensively...
This paper provides a web content-based image searching engine based on SIFT (Scale Invariant Feature Transform) feature matching. SIFT descriptors, which are invariant to image scaling and transformation and rotation, and partially invariant to illumination changes and affine, present the local features of an image. Therefore, feature keypoints can be extracted more accurately by using SIFT than...
Soil erosion is one of the most typical natural disasters in China. However, due to the limitation of current technology, the investigation of soil erosion through remote sensing images is currently by human beings manually which depends on human interpretation and interactive selection. The work burden is so heavy that errors are usually inevitably unavoidable. This paper proposes the technique of...
A novel shape similarity measure based on membership function is proposed in this work to make the measure more consistent with human perception and improve the matching accuracy. The proposed method commences with extraction of feature vectors of shapes in training shape set, then a fuzzy set over each eigenvalue space is defined. The membership function of the fuzzy set is defined and acts as a...
Content-based image retrieval (CBIR) is an effective approach for obtaining desired image, however, due to the semantic gap between low-level visual features and high-level concept of image, CBIR system of state-of-the-art always can't achieve satisfying retrieval performance. In this paper, we propose a novel CBIR system framework. In order to bridge the semantic gap, the mechanism of relevance feedback...
In order to enrich the recommendation of e-commerce functionality and optimize the user experience of online shopping, a new style matching model-based recommend method of e-commerce was proposed. The Content-Based Image Retrieval (CBIR) technology was used to extract the image feature of color, texture and shape of product, calculated the commodity cluster, which have the similar feature of image...
With the development of computer science and the appearance of a great number of medical imaging equipments, large amounts of medical image data is produced in hospitals everyday. More and more medical images represent huge quantities of data that need to be safely stored, automatically processed and retrieved in an intelligent way. Thus people raised that Content-based Image Retrieval (CBIR) technology...
Content-based image retrieval (CBIR) has been an active research topic in the last decade. Using just one kind of feature information may cause inaccuracy compared with using more than two kinds of feature information. Aiming at shape-based image retrieval, in this paper we proposed an image retrieval method using the global and local shape features. Firstly, an image is segmented, and then the compactness...
SAR image retrieval, lacking of well performance recently due to the particularity of SAR image, has drawn more and more attention with the increasing volume of SAR data and the dramatically enlarging application range of SAR image. This paper considers both the characteristic of content-based image retrieval (CBIR) and SAR image, proposing a novel SAR image retrieval method. The proposed method can...
Nowadays, the amount of images increase drastically. Content-based image retrieval (CBIR) has been proposed to efficiently manage these images. Traditional CBIR system extracts the low features of image automatically. Because of the difference between human comprehension and machine, the search results provided by CBIR system always can not satisfy the user's need. So relevance feedback has been used...
This paper presents a similarity match method based on global image and local sub-image using the SIFT features of digital images, and applies our algorithm to Content-Based Image Retrieval. In order to make the SIFT-based image retrieval results better, the most fundamental improvement comes in two areas. One is the introduction of the distance between the matched keypoints, and the shorter the distance...
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