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As a method of image feature extraction, centroid detection algorithm has been applied in many fields. Uncertainty evaluation of centroid detection is an important approach to evaluating the reliability of centroid detection. This paper presents a new method for uncertainty evaluation of centroid detection. The uncertainty associated with the intensity of a pixel, which involves in centroid detection,...
Non-negative matrix factorization (NMF) is an algorithm for decomposing multivariate data into a signal dictionary and its corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and Stodden separability conditions of a dataset and a regular NMF algorithm will fail to decompose it,...
Detection of the fetal electrocardiogram (FECG) from the maternal cutaneous electrode recordings is an important but hard task. To extract the FECG, two important blind source extraction algorithms have been proposed by Barros and Zhi-lin Zhang which using the periodicity and kurtosis, respectively. Barros' algorithm is sensitive for the estimation error of the period of the FECG and Zhi-lin Zhang's...
Blind source extraction is one of the most important problems for multi-sensor networks. We propose a blind source extraction and deconvolution method in the presence of noise. We use MA-model for the signal generation model, and the convolutive observation model. The parameter of MA-model and the observations are obtained from an alternating least square (ALS) algorithm. The reconstruction is done...
Traditional transition region extraction methods depend much on the clip limits Llow and Lhigh. In which methods Llow and Lhigh can not often be obtained correctly from real images, which will result in incorrect extraction of transition region and finally bad quality of segmentation. A novel gradient threshold-based transition region extraction method (GT-TREM) is presented. Transition regions can...
How to obtain effective, reliable characteristic parameter from the limited measured data is a question of great importance in feature extraction. Based on self-adaptive filter action of empirical mode decomposition (EMD) method, this paper drew statistic centre frequency of spectrum of intrinsic modes as new line spectrum characteristic of underwater acoustic signal, and adopted the law of nearest...
As a noteworthy biometric technology, offline palm-print identification plays a very important role in the application of social security. Given a palm-print scanned by a digital instrument, offline palm-print identification needs to perform robust feature matching because of the rotation and distortion existed in input. In our paper we design and implement a minutiae-based offline palm-print identification...
In this paper we propose an approach that utilizes visual features and conventional text-based pseudo-relevance feedback (PRF) to improve the results of semantic-theme-based video retrieval. Our visual reranking method is based on an Average Item Distance (AID) score. AID-based visual reranking is designed to improve the suitability of items at the top of the initial results list, i.e., those feedback...
A new algorithm is developed here for blind extraction of periodic signals. It is assumed that the fundamental frequencies of the sources (or alternatively one of the harmonics for each source) are known a priori. Necessary and sufficient conditions for blind source extraction of cyclostationary signals are introduced and the optimization problem is solved using steepest descent method for complex...
In this paper, we propose a new ICA-based BSS algorithm including estimation of sources' probability density functions (PDFs) to adapt the nonlinear activation function to various noise conditions. In the proposed method, closed-form second-order ICA is introduced as a computational-cost-efficient preprocessing to extract sources' PDFs, which is beneficial for real-time application. Compared with...
Object tracking in computer vision is important. Numerous research papers have been published about this problem. Few references relating to tracking shaped objects via the Hough Transforms exist. This paper provides a method based on the Standard Hough Transform to track rectangular objects. Our method works on edge images obtained by applying the Canny edge detector to the source image. The rectangular...
Corner matching in sequence images serves as a building block of several important applications of stereo vision. In this paper, we establish the corner correspondence between two images in the presence of intensity variations and motion blur by using a fuzzy theory based similarity measure. The matching approach proposed by us needs to extract set of corner points as candidates from both the frames...
Techniques for information hiding and steganography are becoming increasingly more sophisticated and widespread. With high-resolution digital images as carriers, detecting hidden messages is also becoming considerably more difficult. In this paper, we describe a universal approach to steganalyse the least significant bit steganography method for detecting the presence of hidden messages embedded within...
This paper is concerned with the extraction of lip movement image signals from successive image frames. It is suggests the possibility that lip movement image signals can be utilized while detecting the speech block of speech recognition procedures. The image frames are acquired from the PC image camera with the assumption that facial movement is limited during the conversation. First of all, one...
The potential of using satellite imagery for studying oceanic internal waves have long recognized by the oceanographers and remote sensing researchers. A great deal can be learnt about internal waves from satellite data if the grey tone patterns of the Synthetic aperture radar images can be confirmed to correspond to the trough and crest patterns of internal waves. In this paper, a new solution of...
Measuring the similarity between categorical sequences is a fundamental process in many data mining applications. A key issue is to extract and make use of significant features hidden behind the chronological and structural dependencies found in these sequences. Almost all existing algorithms designed to perform this task are based on the matching of patterns in chronological order, but such sequences...
In this paper, a novel technique, based on principal component analysis (PCA), is used to enhance the resonance based target identification process. PCA is used to combine the backscattered signatures of the target from different incident aspect angles. The dominant CNRs of the target are then extracted from the fused signature.
In this paper we propose a new template based feature extractor called Hausdorff Metric Feature Extractor (HMFE). This feature extractor makes use of Hausdorff distance metric for calculating the corner strength. The working of HMFE is justified using the concept of derivatives and gradients. We have also analysed the performance of HMFE under the five criteria: detection, localisation, repeatability,...
At present, the widely applied OCR system has a high recognition for printed texts, however it doesn't have a good recognition schema for formulas. In order to locate and recognize printed formulas accurately, this paper conducted researches according to the following several aspects: use Adaboost method to locate formulas automatically, image processing to obtain thinned formula area, moment method...
Ever since the Federal Communications Commision (FCC) announced that it would open the television (TV) spectrum for opportunistic access, there has been an increased interest in industry as well as academia to come up with proposals that would fit the criteria laid by FCC. To this end, IEEE 802.22 Working Group (WG) is formulating the first worldwide standard for cognitive radio to operate in the...
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