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A major preprocessing step in a multi-script OCR is to identify the script type of the test document image. The published papers on script identification usually assume that the test image is in correct i.e. 0° orientation. But by mistake a document may be fed to the system in wrong orientation, say at an angle of nearly 180° or ±90°. In this method we propose a script identification method that works...
In image classification, the most powerful statistical learning approaches are based on the Bag-of-Words paradigm. In this article, we propose an extension of this formalism. Considering the Bag-of-Features, dictionary coding and pooling steps, we propose to focus on the pooling step. Instead of using the classical sum or max pooling strategies, we introduced a density function-based pooling strategy...
A class of rotation-invariant orthogonal moments is proposed using a complex exponential in the radial direction. Each member of this class, while sharing beneficial properties to image representation and recognition like orthogonality and rotation-invariance, has distinctive properties depending on the value of a parameter, making it more suitable for some particular applications. The computation...
The objective of this study is to investigate different pattern classification paradigms in the automatically understanding and characterizing driver behaviors. With features extracted from a driving posture dataset consisting of grasping the steering wheel, operating the shift lever, eating a cake and talking on a cellular phone, created at Southeast University, holdout and cross-validation experiments...
To distinguish chatter gestation, chatter recognition method based on hybrid PCA(Principal Compenent Analysis) and SVM(Support Vector Machine) is proposed for dynamic patterns of chatter gestation in cutting process. At first, FFT features are extracted from the vibration signal of cutting process, then FFT vectors are presorted and introduced to PCA-SVM for machine learning and classification. Finally...
Mechanomyographic (MMG) signal for prosthetic control has been investigated in recent years and encouraging results in hand-motion patterns identification have been achieved. In this paper, only two accelerometer sensors were used to record the MMG signal in the forearm of fourteen able-bodied people. A kernel generalized discriminant analysis and three linear dimension reduction techniques were applied...
A safe can be made safely by making it key-free. Such a safe can be opened by recognizing the owner's palmprint features only. A new method based on wavelet transform is proposed according to the palmprint line direction and space frequency. A support vector machine classifier is formed by combining radial basis of functions(RBF) kernel with polynomials kernel to significantly improve the rate of...
Multi-kernel learning has become a popular method to allow classification models greater flexibility in representing the relationships between data points. This approach has evolved into localized multi-kernel learning, which creates classification models that have the ability to adapt to a multi-scale feature-space. The advantages of such an approach are often hampered by additional parameters and...
Traditional negative selection algorithms need to calculate the distances between detectors and sample data based on Minkowski distances. As the distance coverage in high dimensional, so the data discrimination will become difficult. In this article, we analyzed the relationship of data dimension and data relative contrast and employed fractional distance calculation method to improve the accuracy...
This paper presents a complete framework for the specification and the detection of patterns as well as the abstraction of kernel traces. We propose a declarative, and easy-to-use scripting language, for the pattern specification. The compiled patterns are then fed-to a detection engine which analyzes the traces, and gradually communicates with an output module to warn the administrator about the...
One of central topics of kernel machines in the field of machine learning is a model selection, especially a selection of a kernel or its parameters. In our previous work, we discussed a class of kernels forming a class of nested reproducing kernel Hilbert spaces with an invariant metric; and proved that the kernel corresponding to the smallest reproducing kernel Hilbert space, including an unknown...
In kernel-based video object tracking, the use of single kernel often suffers from the occlusion. In order to provide more robust tracking performance, multiple inter-related kernels have thus been utilized for tracking in complicated scenarios. This paper presents an innovative method that uses projected gradient to facilitate multiple kernels in finding the best match during tracking under predefined...
Basing on the SVM that is used to solve pattern recognition problems, this paper brings up a new pattern recognition method that combines the kernel K-means Clustering with decision tree SVM. And this method is simpler structure and higher computational efficiency than old one. Meanwhile, this method achieves a good result in the experiment.
Edge of image is one of the most fundamental and significant features. Edge detection is always one of the classical studying projects of computer vision and image processing field. It is the first step of image analysis and understanding. With the continuous improvement of remote sensing image, especially the appearance of Digital Aerial Image, edge detection is necessary step to extract information...
Invariant image representation plays an important role in many pattern recognition applications, such as texture classification, face recognition and character recognition. In this paper, we evaluate some of the invariant orthogonal moments, including Zernike moment (ZM), pseudo-Zernike moment (PZM), and Polar Harmonic Transform (PHT), which are all computed in a circular domain. The performance of...
In Peterson-coil-grounding system(PCGS), the electric parameters in grounding fault have different electric characteristics, and the working situation of PCGS can be recognized by electric parameters of system. In this paper, support vector machines for classification(SVMC)are used to recognize the working situation of PCGS and to detect the fault line or bus. Simulation results show that the method...
Blood vessel segmentation, that is, extraction of the center lines and corresponding local cylinder radii are important for the study of vascular diseases, and in the brain also important for the modeling and understanding of relationships between hemodynamics and electrical neural activity. Several image processing methods have been proposed for vessel extraction in many domains including those that...
Feature extraction is an important step towards pattern recognition. Unsupervised Discriminant Projection (UDP) shows desirable performance for face recognition, but it is unsupervised and the features extracted are correlated; besides it is a linear method in nature. To solve these problems, a new feature extraction method called kernel uncorrelated supervised discriminant projection (KUSDP) is proposed...
This paper presents an iris recognition method based on the two dimensional dual-tree complex wavelet transform (2D-CWT) and the support vector machines (SVM). 2D-CWT has such significant properties as the approximate shift-invariance, high directional selectivity and computationally much more efficient. These properties are very useful in invariant iris recognition. SVM is used as a classifier and...
Using the Mallat fast algorithm with sym5 wavelet, the pulse waves of 20 heroin druggers and 20 healthy normal subjects are decomposed into two levels. The squared distances from the third and tenth scale coefficients in the second-level decomposition of every pulse wave to the global mean value are used to form a feature vector. The extracted feature vectors have good separable characteristics in...
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