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On the basis of explaining the principles of wavelet transform, neural network, and wavelet neural network, the paper examines two methods of face recognition: one is based on neural network, the other is based on wavelet neural network. The paper also offers the features and differences based on algorithmic simulation. The result of the stimulation reveals that face recognition using wavelet neural...
Computer applications require interaction between humans and computers. This interaction has to be lucid and is a challenging task for the traditional devices such as keyboard, optical pen, mouse etc. Hand gestures are more natural, compared with actions associated with the traditional devices. Use of hand gestures to operate machine would make interaction very interesting and easy. Gesture recognition...
Two-dimensional principal component analysis (2DPCA) is a kind of image feature extraction method. The algorithm based on image matrix as the analysis object, before the image feature extraction, it can deal with image data directly and does not need dimension reduction. It process image data without step of vectorization. Although 2DPCA algorithm reduces the computational complexity, it takes up...
A robust fingerprint recognition system based on marginal statistics of 2D wavelet transform is introduced which significantly improves the accuracy of previous wavelet based approaches due to 1) a better selection of features extracted from the wavelet transform, and 2) a more accurate distance measure to find the similarity between fingerprints. A combination of Jain and Poincare algorithms is employed...
Linear Discriminant Analysis (LDA) is one of the principal techniques used in face recognition systems. The Linear Discriminant Analysis (LDA) is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis (PCA) method of face recognition by introducing the concept of classes and distance between classes. This paper...
This study proposed to use wavelet transfer to acquire image features, and use back-propagation neural network to classify type of textile texture. Firstly, wavelet transfer is applied to obtain vertical, horizontal and diagonal images of original image, and compute its wavelet energy to take them as texture features of this image. Finally, the back-propagation neural network is adopted to recognize...
Recently many works focus on the vehicle type recognition because it is important in security and authentication systems. Computational complexity and low recognition rate especially when the system has to recognize among a large number of vehicles, are two major problems in vehicle type recognition. In recent years wavelet and contourlet transform have been applied in the recognition tasks successfully...
In this paper, we propose a contact free system for palm image recognition. Palm images in Red, Green and Blue spectra are used. The method involves multispectral image acquisition using a dedicated setup, pre processing to dynamically locate the region of interest and image fusion using Fourier and wavelet transform based techniques. In pre processing movement of palm in one plane is taken care of...
Character segmentation and recognition are imperative steps in the vehicle license plate recognition (VLPR) system. The skewed license plate affects badly on the accurate character segmentation and recognition. To solve the problem, an efficient approach for skew correction of license plate is proposed based on wavelet transform and principal component analysis. First, a skew feature image of the...
The methods of image edge detection based on the differential, wavelet transform and image morphology are introduced in the paper. Differential operator edge detection method is based on the edge of the adjacent regions' boundary that is not continuous with the gray, using derivative to detect the edge, Wavelet transform edge detection is by means of selecting the appropriate wavelet function to make...
This paper presents an identification-verification biometric system based on the combination of geometrical and palm-print hand features. It attempts to improve the performance of existing hand-geometry or palm-print systems which no combine both methods. 1440 hand images of 144 people with 10 samples each one have been acquired by a commercial scanner with 150 dpi resolution. 80 widths of fingers...
The automatic recognition of images has been always one of preceding issues in the filed of remote sensing. From traditional algorithm of K-Means, maximum likelihood to new decision tree, neural networks, wavelet transform and fuzzy recognition system, the classification accuracy has been improved. In this work, based on Decision Tree Classification (DTC) and Landsat ETM+ data, Ejina Oasis land cover...
A feature extraction algorithm of near-infrared human face based on wavelet transform and 2DPCA (two-dimension principal component analysis) was proposed. This algorithm firstly applied wavelet transform to the near-infrared face images, obtained the low frequency components of face images, and removed high frequency components. Secondly applied 2DPCA to the low frequency components of the face images...
The proposed technique addresses a fusion method of two imaging sensors on pixel-level. The fused image will provide a scene representation which is robust against illumination changes and different weather conditions. Thus, the combination of the advantages of each camera will extend the capabilities for many computer vision applications, such as video surveillance and automatic object recognition...
The image definition identification method based on the composite model of wavelet transform and neural networks is stronger in image edge character extraction, nonlinear process, self-adapted study and pattern recognition. The paper puts forward an evaluation method of image definition based on the focusing mechanism of simulating person's eyes by neural networks and on the composite model of wavelet...
This paper presents an intra-modal fusion environment to integrate multiple raw palm images at low level. Fusion of palmprint instances is performed by wavelet transform and decomposition. To capture the palm characteristics, fused image is convolved with Gabor wavelet transform. The Gabor wavelet feature representation reflects very high dimensional space. To reduce the high dimensionality, ant colony...
For early fire detection, smoke is considered as an important sign for it. Image based detection methods more useful than other methods which use some special sensor devices because of the cost and difficulties in setting them around target areas. When treating the image information of smoke, it is important to consider characteristics of smoke such as the semi-transparency, the non-stationary shape...
The imaging characteristics of infrared and visible light images are different, so the research on fusions of them in the Intelligent Transportation System (ITS) is significant. In this paper the fusions of visual and infrared images on feature level and decision level were discussed. On the feature level, the feature fusion was realized by Wavelet transform, on the decision level, the fusion method...
With the rapid development of modern society and technological progress, using a variety of human organs to identify the needs of growing, due to wavelet decomposition in the airspace and frequency domain can provide good local information, especially in the wavelet decomposition can be reduced the image resolution, and thus a corresponding reduction in computational complexity, the wavelet transform...
Biometrics serves to identify and authenticate individuals and is in many cases replacing current password systems. Its relevance is increasing in many areas of our daily lives, one of them being healthcare. The merits of biometrics to perform e-Health are discussed in this paper. We feel that the optical sensor (fingerprint, finger-vein, face, iris, and retina) using the videophone system is a promising...
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