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A hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for Video OCR is presented in this paper. Video OCR is an important task towards enabling automatic content-based retrieval of digital video databases. However, since text is often displayed against a complex background, its detection and extraction is a challenging problem. In this paper, wavelet transformation is done...
In this paper, we propose a spatiotemporal salient objects-based approach for video retrieval. The spatiotemporal salient object is defined as the region sequence which is spatial salient and temporal continuous at the same time. As attention analysis is an effective mechanism for salient information selection, it provides a practical approach to narrow the semantic gap. Most existing methods extract...
In this paper, we solve the searching problem by high level features used by sign language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left sign and right sign in specific areas. By computing the signs' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the signs' dynamic features. Consequently, we segment...
The mining of images from several categories is a problem arisen naturally under a wide range of circumstances. Image mining concerns with extraction of image data relationships, or other patterns of images which are not explicitly stored in the images. And Image classification is a large and growing field within image processing. Image Classification is useful in CBIR (Content Based Image Retrieval)...
based on the review and summarization of the video retrieval background and related work, this paper studies the key technologies of video retrieval. On this basis, according to the overall system design requirements, it designs a content-based video retrieval system and briefly describes the functions each module achieved. The system is divided into video pre-processing and video query subsystems,...
As a fundamental and critical component of music information retrieval (MIR) systems, automatically classifying music by genre is a challenging problem. The traditional approaches which solely depending on low-level audio features may not be able to obtain satisfactory results. In recent years, the social tags have emerged as an important way to provide information about resources on the web. So,...
Content-based image retrieval is an important research area in digital libraries and multimedia databases. In this paper, we present a novel image retrieval method based on improved Hough transform. First, we developed a new general method of acceleration of the convergence of the Hough transform based. It works on an improvement of the image analysis speed as well as the space undersampling of the...
Relevance feedback has been developed to improve retrieval performance effectively in Content Based Image Retrieval (CBIR). This paper introduces a relevance feedback system for CBIR with both short-term relevance feedback and long-term learning. In short-term relevance feedback, query reweighting algorithm, support vector machines (SVM), and genetic algorithm are adopted. In long-term learning, the...
In this paper, we present a revised method to compute the similarity of traditional string edit distance. Given two strings X and Y over a finite alphabet, an edit distance between X and Y can be defined as the minimum weight of transforming X into Y through a sequence of weighted edit operations. Because this method lacks some types of normalization, it would bring some computation errors when the...
Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases. It is increasingly evident that an image retrieval system has to be domain specific. In this paper, we present an algorithm...
In content-based image retrieval, it is helpful to add a pre-classification module to classify a query image into attentive class or non-attentive class. Based on the pre-classification result, a suitable retrieval strategy is adopted for the query image presented. In this paper, we proposed a Multi-Layer Perceptron (MLP) classifier with the features extracted from saliency map to classify both the...
This paper presents a fast and robust color indexing techniques, namely auto color correlation (ACC) based on a color correlogram (CC), for extracting and indexing low-level features of images. The proposed technique can reduce computational time of color correlogram technique from O(m2d) to O(md). Additionally, an extended technique of ACC based on the autocorrelogram, namely Auto Color Correlogram...
Content-Based Image Retrieval (CBIR) allows automatic extraction of target images from a database of images according to objective visual contents of the image itself. Texture analysis is a popular operation for CBIR. In this paper we propose a texture analysis based scheme for Color Image Retrieval. We use Haar wavelet to decompose color images into multilevel scale and wavelet coefficients. From...
We propose an improved fusion method used in high level feature extraction at TRECVID - average precision based Adaboost (AP-based Adaboost). The AP-based weighting scheme makes use of both the weight and the rank of each sample that all have contribution to the final average precision. The weighting scheme along with the more adaptive formulae modified in our method makes it outperform the standard...
Efficient content-based image retrieval of biomedical images is a challenging problem of growing research interest. This paper describes how X-ray images of the spinal columns are analysed in order to extract each vertebra region. We aim at developing a computer vision tool able to determine a global polygonal region for each vertebra. This is an essential first pre-processing and image segmentation...
Development and practice of content-based image retrieval (CBIR) systems becomes frequent during last decade, in favour of surfers and specialists. However, no recognised system have been dedicated to archaeological purposes, where archeologists try to identify mosaic images with similar content, or need to recognize one or more objects in those images. In this contribution, we propose a new CBIR...
Content-based image retrieval (CBIR) has become a major area of research and received increasing attention. Shape representation and description is one of the major problems in CBIR. This paper outlines and presents a novel boundary-based approach for shape representation and description, which is capable of extracting reliable information of the object outline. Our technique is translation, scale,...
The paper presents a Java based application that implements a series of algorithms for extracting the alphanumeric data and image(s) from the DICOM standard files produced by medical devices. They are stored in a MS SQL server database. A complex querying of this database, based on several criteria: simple text-based or content-based image query on color or texture feature, extracted from color and...
The paper focuses on face image retrieval based on higher level statistical features. The principal independent content feature (PICF) is extracted by independent component analysis (ICA) to represent facial images, and a corresponding similarity measurement is employed. The PICF method encodes face images with locally salient features from a set of training images, which operates in a reduced principal...
Most of the current image database systems depend on visual content to index images, which only provide a partial solution to the image retrieval problem. Natural Scenes are used popularly in our daily lives, which could always cause our strong feelings and senses. This paper discusses how to index natural scenes with season features, one of affective features, to improve the accuracy of image indexing...
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