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Over-segmentation is often used in text recognition to generate candidate characters. In this paper, we propose a neural network-based over-segmentation method for cropped scene text recognition. On binarized text line image, a segmentation window slides over each connected component, and a neural network is used to classify whether the window locates a segmentation point or not. We evaluate several...
Visual saliency plays an important role in biological vision. This paper proposes a novel feature-based approach of visual saliency detection for natural color images. The saliency for each pixel is determined by two features: the structure information and the color information, which represent local information of pixels. The structure information is represented by local steering kernel and the color...
In recent years, with more and more multimedia data being captured and stored, the searching and indexing techniques for multimedia data are getting more attention in the area of multimedia databases. As many research works were done on the content-based retrieval of image and video data, less attention was received to the content-based retrieval of audio data. As one of important parts in audio retrieval,...
As one of important information component in multimedia, audio enriches information perception and acquisition. Analyses and extractions of audio features are the base of audio classification. It's important to extract audio features effectively for content-based audio retrieval. In this paper, based on the theory of rough set, audio features are reduced and a lower-dimension feature set can be obtained...
Automatic target recognition (ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: dimensionality reduction and classifier. After pretreatment on original features a self-organizing neural network trained with the Hebbian rule is used to extract the principal component features. Then a classifier based on directed acyclic graph support vector...
This paper describes a novel multi-connection based anomaly detection system. Previous techniques consume enormous amounts of time due to pre-processing features (unsupervised anomaly detection), or due to the lead time in creating specialized rules (supervised anomaly detection). The system described in this paper, MCAD, uses the observed premise that anomalous connections by one attacker are very...
Audio classification is based on audio features. The choice of audio features can reflect important audio classification features in time and frequency time. The extraction and analysis of audio features are the base and important of audio classification. The most important problem is to extract audio features effectively and make them mutual independence to reduce information redundancy. In this...
Manual labeling, as a conventional audio retrieval method cannot meet the demand of multimedia retrieval for its low efficiency with the explosive growth in the amount of multimedia information. Consequently, content-based audio retrieval is being paid more and more attention so as to improve the efficiency, effectiveness and accessibility of audio retrieval. In this paper, an approach based on general...
Kernel principal component analysis (KPCA), a improving of PCA, is used in face recognition. The paper describes the use of kernel principal component analysis with polynomial kernels to extracts face image features in high-dimensional spaces. KPCA extracts feature set more suitable for categorization than classical Principal Component Analysis does. The experiments on the ORL and Yale face database...
This paper proposes a noise robust content-based music retrieval system for mobile devices. It takes the user's humming/singing audio input and queries the desired songs from music database. Since the system is deliberately designed for mobile devices, noise disturbance are inevitable in practical application. In order to improve the noise robustness of the retrieval system, we propose a new humming/singing...
The main control problem of visual servoing is to cope with the delay introduced by image acquisition and image processing. This delay is the main reason for limited tracking velocity and acceleration. Predictive algorithms are one solution to handle the delay. A predictor is constructed using BP neural network. It is able to estimate the moving target state even if the motion model of the target...
In this paper a novel approach of infrared image small target detection in background of sky and sea is put forward. Firstly, method of line-average-value- subtraction and order morphology filter are used to restrain correlative background and obtain candidate targets; then two different target detection methods are proposed and used to detect targets. One of them is that order morphological edge...
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