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With the explosive growth of Internet image data, labeling image data for image retrieval has become an increasingly onerous task. To that end, we proposed a novel multi-view learning with batch mode active learning framework, MV-BMAL, for improving the performance of image retrieval. Specifically, color, texture and shape features are extracted and considered as un-correlated and sufficient views...
The use of high-dimension features is unavoidable in many applications of image retrieval and techniques of dimension reductions are not always efficient. The space-filling curve reduces the number of dimensions to one while preserving the neighborhood relation. In this paper, Hilbert curve, the most neighborhood preserving space-filling curve, is used in shape retrieval. The retrieving is accelerated...
This research develops the concept of CBIR on the image motif. For processes that do not only find images that have been stored in database, but also be able to recognize some resemblance ornament image or texture as well as form. Although different size, direction of slope, and the layout of texture and shape, but the concept will be recognized. In calculating the percentage of similarity is not...
This paper proposes a technique to construct Image Ontology using low-level features like color, texture and shape. The resulting ontology can be used to extract the relevant images from the image database. Retrieving relevant images from an image database is one of the challenging tasks in multimedia technology. More researches are being done in this area, among them Content-Based Image Retrieval...
This paper proposes Geometric features by which shape and margin characteristics of objects present in images can be extracted. These extracted features are being represented as feature vector of an object and used for defining semantic of an image. These features are invariant to rotation and effectively shape and margin of the objects are defined. The feature are extracted for all the images in...
The contour analysis and identification are the important aspects in visual surveillance research. The paper proposes a fuzzy identification method of contours. First, according to the description of a contour based on the chain-code method, the proposed method utilizes the statistical features of contours including the chain-code entropy and chain-code space distribution entropies, from which the...
Content-based image retrieval (CBIR) has got an intense interest and seen considerable progress over the last decade. But most of the time it is only applied in laboratory. One important reason for this is the diversity of images. Different practical situations call for different taxonomy definitions of images, and lead to very different solutions. At present, and even in the foreseeable future, a...
This paper proposes a service which searches goods by images and finds a shopping mall site that offers referral services. In the service, images are obtained in various types. For image management, it will be modeled using UML Diagram. Unlike other existing sites, the service applied sites have special advantages in:1) Using sketch accessories which enable users to draw pictures.2) Support functions...
The aim of this paper is to increase the success rate of CBIR system with low computational complexity. The success rate of CBIR system depends on localization of the image to be retrieved. This can be achieved by using textons of R, G, B planes of the image which describes the shape. This paper proposes 3 × 3 grids to extract the textons with low computational complexity. The proposed method is based...
This paper introduces a family of rectangularity measures. Several rectangularity measures already exist in literature, and all of them evaluate how much the shape considered differs from a perfect rectangle. But all existing measures assume that all rectangles have the same shape, and a consequence is that these measures do not distinguish among the rectangles whose edge-ration differs. In this paper...
Region-based image retrieval system has been an active research topic in areas such as, entertainment, education, multimedia, image classification and searching. The system decomposes an image into discrete regions and each region is described using primitive features such as color, texture, shape or the combination of them. The extracted regions are indexed and retrieved. One of the key issues with...
Single-feature-based image retrieval system of content-based video retrieval system has a lower performance. In this paper, a algorithm of image retrieval based on NMI invariable feature of dominant color and texture feature is proposed. The shape information and the spatial distribution of dominant color can be described by the NMI invariable feature of dominant color. so the content feature of image...
The modern age is characterized by great professional and private multi-media production of which the largest percentage are images. Search a large number of images from the user's perspective is almost always based on content. The aim of this work is to create a database search algorithm for images that is content based. Starting from the features matrix, algorithm is based on working with color,...
A wide range of properties and assumptions determine the most appropriate spatial matching model for an application, e.g. recognition, detection, registration, or large scale image retrieval. Most notably, these include discriminative power, geometric invariance, rigidity constraints, mapping constraints, assumptions made on the underlying features or descriptors and, of course, computational complexity...
In this paper, we propose an approach for representing both shape and texture information in an image using a single hybrid feature descriptor for Content Based Image Retrieval. Towards this, we compute the gradient magnitude of the input image prior to deriving features. Feature extraction is then performed using the responses from a bank of Gabor filters. Here, we exploit the fact that shape corresponds...
With the increasing volumes of digital image data and the rapid development of internet technologies, it becomes vital to efficiently and accurately retrieve inquired images from the vast available data resources. In this context, content-based image retrieval has been intensively researched in the past decades. In this work, we propose to use contrast and luminance distribution, abbreviated as CoLD,...
The process of retrieving desired or similar images from a large collection of images on the basis of features is referred as Content Based Image Retrieval (CBIR). In this paper, a integrated CBIR system is proposed using combined features and weighted similarity. The features include visual features of color, texture and shape and key text metadata. Some experimental simulations have been presented...
This paper analyzes the characteristics of an experimental otolith retrieval system based on image contours described with Elliptical Fourier Descriptors (EFD). Otoliths are found in the inner ear of fish. Their shape can be analyzed to determine sex, age, populations and species, and thus they can provide necessary and relevant information for ecological studies. The system we propose was tested...
Various types of orthogonal moments have been widely used for object recognition and classification. This paper presents an effective way of extracting texture features, Bessel Fourier moments, for image retrieval and classification applications. The Bessel Fourier moments are calculated for rotation invariance and perform better in terms of represent global features than orthogonal Fourier-Mellin...
To solve the question of the traditional points in image retrieval, a robust and self-adaptive point extraction algorithm is proposed in this paper. The block difference of inverse probabilities (BDIP) image is firstly obtained from the original image based on the BDIP model. According to the distribution feature of the BDIP image, the local points are extracted. Then, the color-spatial feature surrounding...
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