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In this paper, the SIMPLIcity (Semantics-sensitive Integrate Matching for Picture Libraries), an image retrieval system is introduced. The feature extraction is based on Histogram, color layout and coefficients of wavelet transform. This retrieving system adopts feature database for matching so as to reduce the search space which is especially useful in a larger image database. Retrieval images are...
This paper presents a new image feature descriptor derived from the Direct Binary Search Block Truncation Coding (DBSBTC) data-stream without requiring the decoding process. Three image feature descriptors, namely Color Autocorrellogram Feature (CAF), Legendre Chromaticity Moment Feature (LCMF), and Local Halftoning Pattern Feature (LHPF), are simply constructed from the DBSBTC min quantizer, max...
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...
Since last few years, Content Base Image Retrieval (CBIR) system has got more attention from its generic to specific use. CBIR depends upon visual low-level feature extraction i-e color, texture, shape and spatial layout. In this paper, a Local Binary Patterns (LBP) has been employed for texture analysis of image and also it is compared with average RGB color image descriptor method. And then a complementary...
Multiple-query image retrieval is usually utilized in order to enhance performance of the image retrieval system with considering single semantic for a query set. So far, multiple-query image retrieval based on different queries has rarely studied. In this work, we intend to address this problem using a binary component vector. This vector indicates distinct components which exist in an image. The...
Content Based Image Retrieval (CBIR) is the task of retrieving the images from the huge set of database on the basis of their own visual content. Content based image recovery is utilized for the programmed indexing and recovery of images depending on the contents of images called as the elements. This paper gives indicated way to utilize these primitive elements to recover the desired image. The procedure...
An investigation comparative of many descriptors of various images in content-based image retrieval system (CBIR) is described in the paper. This paper describes more number of various features in CBIR system and compare the four different Color and texture based existing low level Feature Extraction Techniques such as Tamura Texture Features, RGP Color Histogram, Gabor Features and Joint Picture...
This paper proposes a filtering system within a large database in order to accelerate image retrieval. A first filter is applied to the database in order to have a small number of candidates. This filter consists of a global descriptor based on color classification. Instead of the use of static classification based on the HVS (Human Visual System), the classification is based on a uniform repartition...
Similarity measures play crucial role in Content-Based Dermoscopic Image Retrieval (CBDIR). This paper analyses and compares images based respectively on twelve distances namely: Minkowski, Euclidean, Standardized Euclidean, Mahalanobis, Manhattan, Chebychev, Cosine, Canberra, Relative Deviation, Bray-Curtis, Square Chord and Square Chi-Squared measures for CBDIR. Two dermatologists were asked to...
Wide range of products such as clothing, bed linen, curtains, and shoes, use fabrics as main raw material. Fabrics have various types of materials, colors and patterns. Harmony in combining the various types of fabrics will affect the beauty of the resulted product. A system that can be used to retrieve some fabrics similar to a fabrics sample automatically will facilitate the combining process in...
Images have become one of the main sources for the information, learning and entertainment; but due to the advancement and progress in multimedia technologies, millions of images are shared daily on Internet which can be easily duplicated and redistributed. Distribution of these duplicated and transformed images causes a lot of problems and challenges such as piracy, redundancy, and content-based...
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...
Due to the increasing variety and quantity of data in databases, retrieving the desired images among massive images storage becomes a challenge. Hence, many image retrieval methods are applied on one or some static datasets and the steps of features extraction and similarity comparison are performed on the dataset images as offline. To address the challenge, we propose an online content-based image...
Computer drawing board is an attractive color exercises platform in the intelligent art teaching module, particularly for foreigner who is difficult to understanding arts literacy background. The process the traditional teaching system need long time required and conventional education facilities would require excessive student carrying capacity. The color-based image art teaching modules in the network...
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 this paper, vocabulary tree based large-scale image retrieval scheme is proposed that can achieve higher accuracy and speed. The novelty of this paper can be summarized as follows. First, because traditional Scale Invariant Feature Transform (SIFT) descriptors are excessively concentrated in some areas of images, the extraction process of SIFT features is optimized to reduce the number. Then, combined...
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...
Almost all existing state-of-the-art pedestrian detection methods use combination of hand-crafted features, which cannot well handle the particular challenges in real-world situation. In this paper, we take advantage of Regions with Convolution Neural Networks features (R-CNN) to extract more robust pedestrian features for effective pedestrian detection in complicated environments. To further improve...
While there are several promising approaches for visual object recognition the application of lightweight devices under varying image conditions and using low quality images still causes lots of problems to be solved. We introduce a new retrieval mechanism including standard orientation sensors helping the visual recognition process. We apply a view based model of the objects and the matching of the...
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