Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Based on a large scale crime scene investigation (CSI) image database, an effective and efficient CSI image retrieval system has been proposed to empower the investigative work of the police force. The main contribution of this paper includes: (1) a DCT domain texture feature extraction algorithm is proposed for CSI images, which is shown to be simple and effective. (2) the use of GIST descriptor...
While much progress has been achieved in the field of content-based image retrieval (CBIR), almost all CBIR techniques operate on pixel data although virtually all images are stored in compressed form. In this invited paper, we present efficient and effective CBIR techniques that operate directly in the compressed domain and thus do not require full decompression for feature extraction. In particular,...
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...
Scale invariant feature transform (SIFT) is effective for representing images in computer vision tasks, as one of the most resistant feature descriptions to common image deformations. However, two issues should be addressed: first, feature description based on gradient accumulation is not compact and contains redundancies; second, multiple orientations are often extracted from one local region and...
Content-based image retrieval, which is based on the principle of deriving visual similarity based on extracted image features, can be useful, especially since most images are unannotated. However, while almost all images are stored in compressed form (most in JPEG format), the majority of CBIR algorithms operate in the uncompressed pixel domain. This not only leads to a computational overhead for...
Content based video retrieval and content-based image retrieval are the hot research topics in recent years. Image feature extraction has played a very important role in the retrieval process. In this paper, we use the image color features and the image fingerprint extracted by the improved perceptual hash algorithm. In order to combine these two features, we have done a lot of tests to find the optimal...
Plagiarism in any form is a serious offense especially in academia and industry where integrity and royalty from work is of utmost importance. In this work, a novel hierarchical feature extraction as well as an approximate nearest neighbor search is proposed for detecting plagiarism of images. The proposed scheme is applicable for natural images as opposed to specific image classes reported in a previous...
A novel region-based method for color scene images characterization is proposed. The method exploits the texture features present in grayscale images extracted by LBP. It superposes a set of ellipses which are generated by rotation and contraction and organized for covering the image, where each ellipse delimits a region of the LBP map. One LBP-histogram is calculated for each region. Finally, texture...
This paper proposes a strategy for content-based image retrieval, which combines unsupervised feature learning (UFL) with the classical bag-of-features (BOF) representation. In BOF, patches are usually represented using standard classical descriptors (i.e., SIFT, SURF, DCT, among others).We propose to use UFL to learn the patch representation itself. This is achieved by applying a topographic UFL...
Visual information on the web, in particular in form of images, is increasing at a rapid rate. Consequently, efficient and effective techniques to retrieve visual information are sought after, especially since users rarely annotate images. In this paper, we present a very fast method for content-based image retrieval of JPEG compressed images. Our method works directly in the compressed domain of...
Content-based image retrieval (CBIR) is a field of active research for almost 20 years. This timeframe has seen several generations of hardware and corresponding changes in computer usage patterns. It is therefore prudent to periodically reevaluate known methods in the context of modern hardware and usage patterns. Overall the issue of resource usage in CBIR is somewhat neglected. In this paper some...
With visual information becoming increasingly important, efficient and effective methods for querying and retrieving this kind of information are highly sought after. In this paper, we focus on image information and querying from image collections in an online retrieval fashion. In online retrieval, image features for performing retrieval are not pre-calculated but need to be extracted during the...
While content-based image retrieval (CBIR) has been an active research area over many years, most CBIR techniques operate in the pixel domain even though images are typically stored in compressed form. Consequently, image decoding is required prior to feature calculation leading to a computational overhead that is prohibitive in particular for the case of online retrieval. However, as has been shown...
In the image retrieval technology, the aim is to retrieve an image based on DCT color coefficients. There were many algorithms based on single feature, presented in past. Those algorithms have lack of speed and require more computational capability. In this algorithm by using DCT, most similar images are retrieved. The idea of DCT was to decouples the color component of image using YCbCr color model...
The discrete cosine transform (DCT) is a widely used technique in content image retrieval. This transform concentrate signal energy into lower order coefficients. In this paper, the construction of DC feature vector and three type of simple binarized feature vectors generated from AC DCT coefficients is presented. Next, in order to capture spatial layout information, annular histograms of introduced...
Based on the analysis of the traditional image retrieval in DCT compressed domain, a novel extraction algorithm is proposed in this paper. The DCT block is firstly classified into different edge type by exploiting five AC coefficients. Then, the edge spatial distribution map is constructed. According to the statistical feature of the map, the edge spatial distribution feature (ESDF) is presented....
A classifier model for satellite image data by using Partitioned-Feature based Classifier (PFC)is proposed in this paper. The PFC does not use concatenated feature vectors extracted from the original data at once to classify each datum, but uses extracted feature vectors to classify data separately. In the training stage, the contribution rate calculated from each feature vector group is drawn throughout...
This paper deals with a fragile watermarking technique for the authentication of medical images. Medical images are stored in archiving and communication systems that are accessed by the radiologists for diagnosis. The proposed method insure the integrity of the medical image data that is being transferred over public network. Any modification to the watermarked image can be detected using the proposed...
In automatic image annotation, it is often extracting low-level visual features from original image for the purpose of mapping to high level image semantic information. In this paper, we propose a novel method which integrates kernel independent component analysis (KICA) and support vector machine (SVM) for analyzing the semantic information of natural images. KICA, which contains a nonlinear kernel...
This paper proposes an efficient content-based image retrieval scheme based on Semantic Object Detection (SOD). The feature extraction process uses quantized discrete cosine transform (DCT) blocks where the retrieval of the query image is performed using a histogram-based similarity measure. SOD aims to reduce the size of the database from which the retrieval of similar images is conducted. The use...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.