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This paper presents a framework that uses ear images for human identification. The framework makes use of Principal Component Analysis (PCA) for ear image feature extraction and Multilayer Feed Forward Neural Network for classification. Framework are proposed to improve recognition accuracy of human identification. The framework was tested on an ear image database to evaluate its reliability and recognition...
Document Script Identification (DSI) is a very useful application in document processing. This paper presents a method for this application that uses a new noise tolerant feature, the Downgraded Pixel Density feature. Compared to other features widely used in existing DSI solutions, this new feature is much more robust to variations in slant, font and style of printed documents. Experimental results...
Feature extraction for the dimensionality reduction of hyperspectral data is performed by means of Auto-Associative Neural Networks. The algorithm performance is compared to the Principal Component Analysis and the Maximum Noise Fraction ones. Results of land cover pixel-based maps yielded by the reduced vector and a dedicated neural network classification algorithm are also reported.
Nowadays personal identification is a very important issue. There is a wide range of applications in different spheres, such as video surveillance security systems, control of documents, forensics systems and etc. We consider a range of most significant aspects of face identification system based on support vector machines in this paper. At first we propose improved face detector to get the region...
Line matching is useful in many computer vision tasks such as object recognition, image registration, and 3D reconstruction. The literature on line matching has advanced in recent years, nevertheless, compared to other features (such as point and region matching approaches) it has made little progress. Especially, very few algorithms address the problem of image scaling. In this paper, we present...
In this paper, we propose a face detection framework that combines both feature, and skin pixel approaches, while making the framework self adaptive which is important for non controlled environmental conditions. The framework uses skin color information to reduce the search space for faces by localizing the probable skin regions using a mixture of multivariate Gaussians whose parameters are first...
In this paper the potential of neural networks has been applied to hyperspectral data and exploited either for classification purposes or for data feature extraction and dimensionality reduction. For this latter task, a topology named autoassociative neural network has been used. In its complete form, the processing scheme uses a neural network architecture consisting of two stages: the first stage...
Palmprint is one of the relatively new physiological biometrics due to its stable and unique characteristics. The rich texture information of palmprint offers one of the powerful means in the field of personal recognition. The proposed system is based on geometrical features and texture features extracted using kernel principal components analysis (K-PCA). In the coarse-level stage, the hand geometrical...
This paper presents a new no-reference perceptual blur metric by using the radial basis function network which is based on the orthogonal least squares learning algorithm (OLS-RBF). It extracts the generalized local features of the edge points in structure-texture region and acquires the generalized image features by performing Principal Component Analysis (PCA) on the average of generalized local...
The fact that the signature is widely used as a means of personal verification emphasizes the need for an automatic recognition system. Recognition can be performed either offline or online based on the application. Online systems use dynamic information of a signature captured at the time the signature is made. Offline systems work on the scanned image of a signature. In this paper we present a method...
Multi-focus image fusion aims at overcoming imaging cameras' finite depth of field by combining information from multiple images with the same scene. In this paper, a regional firing intensity (RFI) is defined, which is based on the statistical characteristic in local window of neuron firing times when pulse coupled neural networks (PCNN) is utilized in the image fusion. A novel image fusion algorithm...
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