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Image retrieval and classification in medical domain are the two important aspects in decision making and automatic annotation of benign and malignant images. These processes improve the decision making during decease identification. Image classification is usually done by checking image visual or semantic content similarity. Image content may be represented by its low level visual features referring...
Content Based Image Retrieval (CBIR) aims to retrieves images in the database that are similar to a query image based on the contents of the image rather than metadata. The algorithm used to extract features from images is one of the most influential factors towards a CBIR system's performance. In this paper, we take a look at hybrid information descriptors (HID) as the feature extraction algorithm...
Nowadays information retrieval systems get more attention due to the increasing use of multimedia technologies. The information may be in the form of video, image, sound and/or text. Application of surveillance, digital libraries, web applications and various other applications that handle enormous volume of data essentially have information retrieval components. This paper demonstrates an image retrieval...
Growth of the image mining arena calls for the need of quality image retrieval techniques in par with the human perception which are invariant to scale and rotation. An optimized content based image retrieval system based on local visual attention features to bridge the semantic gap problem is proposed. The approach involves the salient point detection using Scale Up Robust Features (SURF) detector...
In this paper we use the Earth Movers Distance (EMD) algorithm to measure similarity between shapes for recognizing and searching Arabic words. We have used the Shape Context and the Angular Radial Partitioning descriptors to evaluate matching and recognizing with EMD. Based on the encouraging results of high accuracy and recall, we follow the low-distortion embedding of the Earth Mover's Distance...
Traditional design patent verification based on manual comparison is too labor-intensive, time-consuming and subjective to be applied efficiently in practice. Design patent image retrieval system is designed to retrieve some similar patent images with much visual similarities. Structured features and multiple feature fusion are two main technologies to ensure the retrieval accuracy in the system....
Different image has different characteristic attributes. And the similarity between images is the measure distance of these characteristic attributes. Three kinds of similarity metric models, which are the models based on histogram statistic, based on pixels and based on the differences between pixels, were described. Then the performances of these three kind models have been analyzed from various...
Content-based image retrieval systems have become a reliable tool for many image database applications. There are several advantages of the image retrieval techniques compared to other simple retrieval approaches such as text-based retrieval techniques. This paper proposes an image retrieval technique that can be used for retrieving color images. In this paper, we propose two variations of an image...
In this paper, we evaluate several low dimensional color features for object retrieval in surveillance video. Previous work in object retrieval in surveillance has been hampered by issues in low resolution, poor segmentation, pose and lighting variations and the cost of retrieval. To overcome these difficulties, we restrict our analysis to alarm-based vehicle detection and as a consequence, we restrict...
In this paper we survey two multi-dimensional Scale Saliency approaches based on graphs and the k-d partition algorithm. In the latter case we introduce a new divergence metric and we show experimentally its suitability. We also show an application of multi-dimensional Scale Saliency to texture discrimination. We demonstrate that the use of multi-dimensional data can improve the performance of texture...
This paper presents a codebook learning approach for image classification and retrieval. It corresponds to learning a weighted similarity metric to satisfy that the weighted similarity between the same labeled images is larger than that between the differently labeled images with largest margin. We formulate the learning problem as a convex quadratic programming and adopt alternating optimization...
We present a new algorithm for a robust family of Earth Mover's Distances - EMDs with thresholded ground distances. The algorithm transforms the flow-network of the EMD so that the number of edges is reduced by an order of magnitude. As a result, we compute the EMD by an order of magnitude faster than the original algorithm, which makes it possible to compute the EMD on large histograms and databases...
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