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Retrieval of user interested images based on pictorial queries is an interesting and challenging task. This paper proposes an Improved Region based image retrieval system using FCM & multiple shape, texture features. The Proposed system uses Fuzzy c-means clustering algorithm for image segmentation. Local Binary Pattern (LBP), Hu moments and Radial Chebyshev Moments are used in this work. For...
This paper proposes a novel method of recognizing plant leaf image using a combination of venation and contour features. In this method, the shape is cut into pieces under different scales to describe the leaf image in a multiscale way. Both leaf venation and contour features extracted from the cut pieces are utilized to provide comprehensive description under each scale. The performance of the proposed...
In this paper, we present a new method to sketch the common among several images. Our method captures rotation invariance by extending the local self descriptor to rotation invariance and proposes a easy method to detect a roughly similar region across the images. Our method is composed of three stages: (i) Detecting a similar region which the proportion of the common is as large as possible across...
In recent years, the medical image retrieval play an important role in the field of medical diagnosis. The primary goal is to retrieve accurate matching images from the database. In order to achieve this goal, quite a few methods were used in the past years and some of them can get realistic results. However, after some deep and further experiments, we found that some classic feature descriptors or...
Most retrieval systems are mostly based on key words for image search, but in many case it cannot meet demands for different user with different view. In this paper, a new approach of content based image retrieval (CBIR) is presented, which is based on the image frequency content. Indeed, we have used the 2-D ESPRIT (Estimation of Signal Parameters via Rotationnal Invariance Techniques) method to...
Most of the traditional sketch-based image retrieval systems compare sketches and images using morphological features. Since these features belong to two different modalities, they are compared either by reducing the image to a sparse sketch like form or by transforming the sketches to a denser image like representation. However, this cross-modal transformation leads to information loss or adds undesirable...
In this paper an extraction of intensity variance and size-intensity mean features is considered. Their effectiveness is compared for texture image searching.
The multimedia databases are becoming more and more popular nowadays. One of their main problem is a huge data amount storage. Another problem with multimedia databases is querying. Traditional approaches, based on textual keywords are not sufficient. More advanced techniques, incorporating image content features, should be used. In this paper we propose new multimedia database structure with ability...
In Content-Based Image Retrieval (CBIR) Systems it is necessary to combine more than one visual descriptor in order to improve the retrieval performance. The most common descriptors are Color-Based, Shape-Based and Texture-Based descriptors. When more than one visual descriptor is linearly combined, some adequate weight must be assigned to each visual feature. The most common manner is setting the...
The paper presents a sketch-based image retrieval algorithm. One of the main challenges in sketch-based image retrieval (SBIR) is to measure the similarity between a sketch and an image in contour with high precision. To tackle this problem, we divided the contour of image into two types: the first is global contour, suggesting that we can use it to reduce the similarity between the images with complex...
The retrieval of visual cultural symbols is an important research field of inheriting and carrying forward Chinese traditional culture in digital way. Generally visual cultural symbols are foregrounds of natural images, so using shape features in image retrieval that needs image segmentation in advance has great advantages. At present, image segmentation is mostly interactive, which is quite subjective,...
This paper presents a retrieval method for the image of Chinese characters calligraphy. The precision and recall rate are main indicators to measure the quality of image retrieval algorithm. Starting from the two aspects, there are two parts in the process of image retrieve which is proposed in this paper. In this paper, carry out the retrieve with the Hu invariant moment matching algorithm, which...
This paper describes an multi-features indexing system for use in Content Based Image Retrieval. The standard CBIR approach is simple and usually use a single information such as shape, scale or color, which leads to recognition problems in some cases, to remedy this problematic, we use additional features to combine types of information. From many points of view local descriptors are relatively different,...
The paper contributes to the CBIR systems applied to trademark retrieval. The proposed model uses Scale Invariant Feature Transform (SIFT) and includes aspects from visual perception of the shapes, by means of feature extractor associated to a non-symmetrical perceptual zoning mechanism based on the Principles of Gestalt. We carried out experiments using four different zonings strategies for matching...
Image retrieval plays a major role in security systems to extract the images with similar features or patterns, to retrieve the relevant images in web search engines, in industries to detect crack in the manufactured parts, in architectural designs to find same texture patterns and so on. To accomplish efficiency in all the fields of image processing, the effective image retrieval mechanism is imminent...
Histograms of Oriented Gradients (HOG) feature has been successfully used in pedestrian detection and achieves high accuracy. This paper introduces a content retrieval algorithm based on improved HOG. The method has two steps which are adjusting the HOG structure by scanning the image with a sliding HOG window and reducing feature dimension by principle component analysis (PCA) technique. The experimental...
In order to realize the content-based image retrieval (CBIR), some characteristics of the images should be extracted like color, texture and shape. The extremely important thing in CBIR is to search the most similar database images to match the query image, which needs to improve the precision. This paper proposes an Improving Precision Priority (IPP) algorithm integrating vital features and the query...
Contour-based Fourier descriptors are very simple and effective shape description method used for content-based image retrieval. Similarity between Fourier descriptors is usually computed using measures such as City-block or Euclidean distance. These similarity measures consider all harmonics to be equally important, therefore harmonics with larger magnitude tend to have larger significance during...
In this paper we describe Query-by-Shape, a new Content-Based Image Retrieval interface. In this method objects are decomposed into features, each feature may consist of a color, a texture or a shape attributes. The query stage consists of comparing the query objects graph with objects from the database. The main advantage of the proposed solution is the ability to query for an object without having...
In this paper, we have hybridized the three main techniques of Content Based Image Retrieval (CBIR) in order to increase the efficiency and precision of the images which are retrieved. Firstly, the color quantization of the image is done with the help of ColorCorrelogram Vector. The spatial arrangement of the color pixel is also determined by the colorcorrelogram. Then, the shape and texture of the...
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