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This paper proposes a novel content based image retrieval system incorporating the relevance feedback technique. In order to improve the retrieval accuracy of content based image retrieval systems, research focus has been shifted in reducing the semantic gap between visual features and the human semantics. The five major techniques available to narrow down the semantic gap are: (a) Object ontology...
This paper describes a novel method for extracting features of batik images. This method is called enhanced micro-structure descriptor (EMSD). EMSD is the enhanced model of micro-structure descriptor (MSD) which proposed by Guang-Hai Liu. Different with MSD that uses only edge orientation similarity for creating micro-structure map and then utilises this map along with color values; EMSD adds a new...
The vast growth of Internet and digital contents of Internet creates much interest on automated image indexing and retrieval techniques. Most commercial Content Based Image Retrieval systems use color histograms as one of the features. In this work, we have prepared combined color histograms for three regions (top, bottom and middle) of the image. The combination of those histograms will indirectly...
Content-based image retrieval (CBIR), also known as query by image content is one of the applications of computer vision. In CBIR, the contents derived from the image like color, shapes, and textures are analyzed rather than the metadata such as keywords, tags, and/or descriptions associated with the image. In this paper, the texture features of the image are modelled using Generalized Gaussian Distribution...
In content based image retrieval (CBIR) system, target images are sorted by feature similarities in terms of related query. Image classification is the important field in applications like security, biometrics, and in medical applications. An efficient image retrieval system is Hue, Saturation and Value (HSV) color space. This Classify the image into n number of areas based on different selected ranges...
In this paper, we propose a new method for cartoon image retrieval based on the local invariant shape feature, named Scalable Shape Context. The proposed feature uses the Harris-Lap lace corner to localize the key points and corresponding scale in the cartoon image. Then, we use Shape Context to describe the local shape. The feature point matching is achieved by a weighted bipartite graph matching...
In recent years, content-based image retrieval achieved continuous development, but in the previous studies, only the relevance is cared in retrieval system, so many duplicate or near duplicate documents retrieved in response to a query and cannot satisfy the users. To solve this problem, we propose the Content-based Diversifying Plant Image Retrieval in this paper. In order to make the retrieval...
This paper presents a simple yet efficient image retrieval technique that defines image feature descriptors using localized multi-text on histogram. The proposed technique extracts a unique feature vector for each image in the image database based on its shape, texture and color. First, the image is divided into smaller equal size blocks and then for each block texture orientation is computed independently...
In this paper, we developed the system for recognizing the orchid species by using the images of flower. We used MSRM (Maximal Similarity based on Region Merging) method for segmenting the flower object from the background and extracting the shape feature such as the distance from the edge to the centroid point of the flower, aspect ratio, roundness, moment invariant, fractal dimension and also extract...
The paper mainly investigates the widely-used image features and related feature selection methods in content-based image retrieval (CBIR).The texture features and shape features that could be used in the retrieval of solar images are mainly discussed. The result of the survey indicates that although the CBIR related research work in solar image retrieval is comparatively less, the existing achievements...
Image retrieval tools can assist people in making efficient use of digital image collections; also it has become imperative to find efficient methods for the retrieval of these images. Most image processing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In very big image databases, image processing takes very long time for run on a single core processor...
This paper addresses the problem of automated prosthesis modelling and manufacturing, whose machining parameters are based on images extracted from different medical databases. The specific case of 3D surface restoration of a defective skull was used as study case. A method based on adjusted ellipses on skull bone curvature performs the symbolic representation of searching parameters. The superellipse...
Shape is a distinguishing feature of objects. But when objects have similar global shapes, discriminating them becomes difficult. This calls for the identification of important parts of the shapes. In this paper, we introduce the concept of discriminative parts and propose a method to identify the same. We show how levels of importance can be assigned to different regions of contours, based on their...
The issue of near duplicate document image retrieval is addressed in this paper, which is characterized by not only encoding each individual word in the image but also modeling its local spatial configuration. On representing each word in the image as a string in terms of its shape characteristics, a lexicon is first learnt from a training set. Then a word in an arbitrary document image can be soft...
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...
In this paper, we propose a fast large-scale signature matching method based on locality sensitive hashing (LSH). Shape Context features are used to describe the structure of signatures. Two stages of hashing are performed to find the nearest neighbours for query signatures. In the first stage, we use M randomly generated hyper planes to separate shape context feature points into different bins, and...
The main objective of Content-Based Image Retrieval (CBIR) systems is to retrieve a ranked list containing the most similar images of a collection given a query image, by taking into account their visual content. Although these systems represent a very promising approach, in many situations is very challenging to assure the quality of returned ranked lists. Supervised approaches rely on training data...
We introduce a statistical shape descriptor for Sketch-Based Image Retrieval. The proposed descriptor combines feature information in near and far support regions defined for each sketch point. Two feature values are extracted from each point, corresponding to near and far support regions from the point's perspective, and used to populate a 2-D histogram representing the shape features of the sketch...
Efficacious retrieval of similar shapes from large image databases is still a challenging problem. In recent works about shape retrieval, methods based on Dynamic Space Warping (DSW) and descriptors with contour information have had a significant presence. This paper introduces a technique for Content-Based Image Retrieval (CBIR) that encompasses a robust corner detector and a new shape descriptor...
Digital images have many applications in different fields like medical imaging and diagnostics, weather forecasting, space research, military etc. The number of images available and their wide variety increases with the ease of acquiring, storing and sharing digital images due to the advances in technology. As a result, the significance of image retrieval algorithms and systems has been considerably...
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