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Local patterns have two problems: 1) the traditional local patterns methods only consider the frequency of each pattern, and does not consider the co-occurrence information between adjacent pixels pairs in the image; 2)the traditional methods limit on the gray texture analysis, ignoring the importance of color information. To address above problems, a novel method is proposed for color image retrieval...
Feature extraction simplifies the amount of information needed to describe the properties of an image accurately. This paper measures the performance of a CBIR system based on texture feature against combination of both color and texture feature. A Gray Level Co-occurrence Matrix is calculated for computing the texture feature of an image. Using these textual parameters similar images are extracted...
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...
This work is focused on the modeling and development of a CBIR (Content-based image retrieval) system applied to the recovery of digital medical images of a human body, denominated M-CBIR. This model is composed on two methodologies: features extraction techniques and metric data structures. When this set of techniques is applied to the search of different human body regions, it can retrieve the most...
We have become able to get enough approvable images of a target object just by submitting its object-name to a conventional keyword-based Web image search engine. However, because the search results rarely include its uncommon images, we can often get only its common images and cannot easily get exhaustive knowledge about its appearance (look and feel). As next steps of image searches in the Web,...
Magnetic resonance spectroscopic imaging (MRSI) integrates both spectroscopic and imaging methods to produce spatially localized spectra from within the sample or patient. Although MRSI is a relatively new imaging technology for clinical applications and relevant databases still do not exist, the rapid advances made in the field of NMR and the associated scanning technologies, the increased frequency...
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...
Carotid plaques are the main cause of neurological symptoms due to distal embolization or flow reduction. An objective classification of such lesions into symptomatic or asymptomatic is crucial for optimal treatment planning. The paper proposes a diagnostic framework to tackle this problem which consists of image processing, plaque detection, feature extraction and classification using AdaBoost in...
In this paper, we propose a new representation and matching scheme for wood image retrieval using scale invariant feature transformation (SIFT). We extract SIFT feature points in scale space and perform matching based on the texture information around the feature points using SIFT feature operator. This scheme can be appended to most existing wood image retrieval systems and improve their retrieval...
As is known to all, there are many kinds of wood. If we distinguish the wood's characteristics by our eyesight, we can't distinguish the category and property of the wood correctly, and this way will cost enormous workload. In this paper, we propose the keyblock distribution based wood image retrieval algorithm, in order to make the wood image retrieval algorithm more precise and objective. Keyblocks...
Context plays a valuable role in any image understanding task confirmed by numerous studies which have shown the importance of contextual information in computer vision tasks, like object detection, scene classification and image retrieval. Studies of human perception on the tasks of scene classification and visual search have shown that human visual system makes extensive use of contextual information...
Research on image retrieval technology based on color feature, for the color histogram with a rotation, translation invariance of the advantages and disadvantages of lack of space, a color histogram and color moment combination image retrieval. The theory is a separate color images and color histogram moment of extraction, and then two methods of extracting color feature vector weighted to achieve...
Content-based image retrieval (CBIR) considers the characteristics of the image itself, for example its shapes, colors and textures. The current approaches to CBIR differ in terms of which image features are extracted. Recent work deals with combination of distances or scores from different and independent representations. This work attempts to induce high level semantics from the low level descriptors...
This paper proposes a new image retrieval method using non-separable discrete wavelets (NDWT) and local binary patterns (LBP). Compared with the traditional wavelet, the three high frequency sub-images generated by the non-separable wavelets can extract more information and do not extensively focus on the three special directions any more. Further, local image texture and their occurrence histogram...
In perceptually uniform color space, color differences can be measured in a way close to the human perception of two colors. A new feature descriptor, namely the color textons descriptor, is proposed in this paper according to the attribute of perceptually uniform color space. This descriptor can represent features via color differences in textons component images. It converts color image from RGB...
To overcome the disadvantage of describing contents of an image only with global features, a new color cluster image retrieval algorithm based on object regions is proposed. In this paper, firstly, object regions are extracted from an image, and then a new color cluster algorithm is presented. The algorithm is developed based on HVS color space, histogram intersection and combination of two similarity...
A new geometric constraints histogram descriptor (GCHD) based on curvature mesh graph for image retrieval is presented in this paper. Through this method, the edge and angle geometric constraints based on the curvature mesh graph are extracted firstly. Then the histogram algorithm is applied on the geometric constraints to obtain the histogram matrix for each curvature point. Finally, the histograms...
In this paper we propose a method for semantic inter-media photographic retrieval, exploiting the advantages of both textual and content-based frameworks: the relatively high initial precision and diversity of results from visual and text retrieval, and the robust overall precision and recall of text retrieval. The method employs simple block-based visual retrieval which, at early precision, outperforms...
To make the HSV color model more suitable for wood image retrieval, one hundred images of wood were analyzed to educe their visual spatial distribution laws in HSV color space. It was found that hue, saturation and value components of wood were all centralized distribution. Based on the histogram threshold segmentation and color perception, the proposal on non-equal spacing division of hue, saturation...
Logo or Trademark is of high importance because it carries the goodwill of the company and the product. Products are mostly recognized by their brand logos. Their recognition is a major problem. A number of techniques are there for logo recognition. In this paper, a number of invariant techniques are compared to find out their effectiveness on various categories of brand logos. Techniques which were...
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