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Predicting stock price is an important task as well as difficult problem. Stock price prediction depends on various factors and their complex relationships, which is the act of trying to determine the future value of a company stock. The successful prediction of a stock future price could yield significant profit. This paper demonstrates the applicability of a framework that combines support vector...
The palmprint recognition has become a focus in biological recognition and image processing fields. In this process, the features extraction (with particular attention to palmprint principal line extraction) is especially important. Although a lot of work has been reported, the representation of palmprint is still an open issue. In this paper we propose a simple, efficient, and accurate palmprint...
Commercial websites usually contain noisy information blocks along with main content. Noisy information degrades the performance of web content mining. Web content mining is used for discovering useful knowledge or information from the web page. In this paper, we propose noise elimination method that uses tag based filtering followed by structural analysis of the web page. The proposed tag based filtering...
The capture of data provenance is a fundamentally important task in eScience. While provenance can be captured using techniques such as scientific workflows, typically these techniques do not trace internal data manipulations that occur within off-the-shelf analysis tools. Yet it is still essential to capture data provenance within such environments. This paper discusses an in situ provenance approach...
Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the...
Introducing the similarity discovery algorithm based on time series into virtual throwing action recognition is a new attempt. Four key sub-patterns from the whole throwing action process were defined, and the corresponding sub-patterns discovery algorithms were designed. The similarity matching between the target time series and the template was done to implement the recognition of virtual throwing...
Both wavelet algorithms and empirical mode decomposition (EMD) signal analysis method have strong power discriminate the signals from the noise, but the precision of denoise is affected by the end errors of EMD, the effect is more serious especially when the signal carries the information of the trend development. Based on the capability of orthogonal wavelet transform in de-noise, trend extract function...
Multipath effects on carrier phase measurements are the major error source for short baseline positioning. Multipath effects impair the precision and reliability of both the ambiguity resolution and estimated site coordinates. Empirical Mode Decomposition (EMD) is a relatively new non-linear technique for adaptively representing non-stationary signals. The method is a fully data driven approach. Noisy...
An anisotropic smoothing algorithm for removing noise of triangular mesh models is proposed. First, the desirable normals of the triangles are approximated using our desirable normal computing schemes, and then each vertex is repositioned according to desirable normals of adjacent triangular faces. The desirable normals estimated by a weighted sum of normals at neighboring faces. If the face differs...
This research proposes new system which finds the music by using Query-by-humming (QBH). For finding a stored music, the features of humming data are selected by using G.729 feature extractor. We normalize the extracted features by using mean-shifting, median filtering, average filtering and min-max scaling methods. Then the corresponding music is matched based on dynamic time warping (DTW) algorithm...
The linear canonical transform (LCT), which is a generalization of the classical Fourier transform and fractional Fourier transform (FRFT), is an important time-frequency analysis tool. It can analyze the signal in between the time and frequency domains. In this paper, we first introduce the LCT and a number of its properties and then discuss the LCT's relationships with time-frequency representations...
In this paper, we propose image enhancement of microarray images using histogram specification method. The proposed approach consists of system model that discuss about finding the type of noise present in the image and enhancing image by removing the noise present in the image. The proposed method is very efficient as it enhances image by revealing most of the microarray spots which is used for subsequent...
3D reconstruction based on high-level features, such as line and plane, is an important development trend in Digital Photogrammetry and Computer Vision. A novel method for extracting stratight line is presented, which can be illustrated as follows. Firstly, image is preprocessed by Wallis filtering that is used to enhance the image contrast and reduce the noise, so it is easy to extract more lines...
This paper studies median filtering algorithm and several related fast algorithm proposed by other professors, then gives a novel fast algorithm of median filtering based on divide-and-conquer method and improved-choose-sort method. In new algorithm, all the pixels in filtering window are divided into several blocks, the median values of each block are computed using improved-choose-sort algorithm,...
In this paper, a method of detecting industrial bearing's quality based on image edge morphologic analysis and recognition technology was proposed. The image filter, enhancement and segmentation were adopted to pre-process the image and a novel image coding method based on relative direction coding was presented as well. Furthermore, an improved method based on image edge morphologic analysis was...
The biometrics identification technology based on vein pattern has being developed rapidly in recent years. However, the vein image acquired by near-infrared (NIR) imaging device has low contrast and usually has a mount of noise which make an effective image segmentation be a great challenge. Thresholding is a popular vein image segmentation method, which is easy to calculate and can shorten the recognition...
This paper describes an automated technique to extract defects in photomask images. Conventional approaches to photomask inspection rely on difference based techniques which are susceptible to distortion from image `noise'. We propose a robust method based on high order moment (HOM) between reference and test images. In comparison to difference based methods, HOM reveals a wide distribution range...
This paper presents a fast algorithm to detect the road lines and the road edges of structured and unstructured roads, respectively. In structured road detection, we firstly utilize vertical Sobel mask and color characteristic to detect the points of road lines. If the number of points is greater than a predefined threshold, we refine the detection results with slope filtering. And the least square...
This paper specifies an OCR system for printed Malayalam characters. Malayalam is the principal language of the South Indian state Kerala. The input to the system would be the scanned image of a page of text and the output is a machine editable file. Malayalam Character recognition is a complex task because of the presence of two scripts; old script and new script and a lot of combinational characters...
A new method is proposed for speckle noise suppression and water objects extracting from synthetic aperture radar (SAR) imagery based on sequential nonlinear filtering and independent component analysis. The distribution of SAR image data with multiplicative speckle noise is non-Gaussian and its parameters are unknown. Logarithmic quantification is utilized to transform multiplicative speckle noise...
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