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Automatic image annotation or image classification can be an important step when searching for images from a database. Common approaches to medical image annotation with the Image Retrieval for Medical Applications (IRMA) code make poor or no use of its hierarchical nature, where different dense sampled pixel based information methods outperform global image descriptors. In this work we address the...
Data from medical imaging system need to be analysed for diagnostics and clinical purposes. In a computerized system, the analysis normally involves classification process to determine disease and its condition. In an earlier work based on a database of 315 fundus images (FINDeRS), it is found that the foveal avascular zone (FAZ) enlargement strongly correlates with diabetic retinopathy (DR) progression...
In this paper, we propose to exploit the symmetrical characteristic of the face to represent and classify face images. The proposed method first partitions each face image into two halves, i.e. the left part and the right part of the face image. The method then uses a linear combination of the left parts of all the training samples to represent the left part of the testing sample. Also, this method...
Verification of subjects using their unique physiological features has recently attracted much attention to develop secure biometric systems. One of the most reliable physiological features is electrocardiogram (ECG) waveform, which is the electrical reflection of the heart activity, and has a unique characteristic for each individual. In this paper, autoregressive (AR) coefficients along with mean...
In statistical pattern recognition, high dimensionality is a major cause of the practical limitations of many pattern recognition technologies. Moreover, it has been observed that a large number of features may actually degrade the performance of classifiers if the number of training samples is small relative to the number of features. This fact, which is referred to as the “peaking phenomenon”, is...
This paper presents an algorithm to extract the region of interest (ROI) from the palm print image of the Hong Kong PolyU large-scale palm print database (version 2). Competitive coding method is used for feature extraction. Coding based methods are among the most promising palm print recognition methods because of their small feature size, fast matching speed, and high verification accuracy. Competitive...
Face is an important biometric feature for personal identification. This paper describes a new face verification method based on singular value decomposition and RBF neural networks. The proposed method utilizes the positive samples and negative samples learning ability of RBF neural networks to improve the principal component analysis (PCA) based face verification. Experiment results show that the...
Linking a person based on handwritten documents is one of the oldest techniques that is used by crime investigators and forensic scientists. The importance of writer recognition in anthrax letter cases has made this examination popular in recent years. In this paper we propose four feature set namely directional opening, directional closing, direction erosion and k-curvature features for writer recognition...
In practical applications, errors should not be treated equally, but conditionally. In this paper, errors are categorized based on different costs in misclassification. Accordingly, the characteristics of the error categorization and the corresponding strategies for correcting them are proposed. Verification based on Arabic Handwritten Numeral Recognition is considered as one application to utilize...
In this paper we present two novel off-line signature verification systems, constructed by combining an ensemble of eight base classifiers. Both score-based and decision-based fusion strategies are investigated. Each base classifier utilises the novel flexible grid-based feature extraction technique proposed in this paper. We show that the flexible grid-based approach consistently outperforms the...
In this paper, we consider the task of automatic handwritten mail classification and we investigate the relation between the transcription rate and the classification rate. Several configurations of a multi-word handwriting recognizer using different language models are tested and their word recognition rates on the documents to be classified are reported. For the document classification task, we...
A method for Off-line handwritten signature verification is described in this paper. Recently, several papers have proposed pseudo dynamic methods based on the ink deposition process to discriminate between genuine and fake signatures. The major problem of those methods is the ink texture normalization in order to make the system invariable to the pen. The more extreme pen normalization is the binarization...
In this paper, the higher-order random projection (HORP) is proposed to directly project the higher-order tensor object from high-dimensional space to low-dimensional space for recognition task. In traditional random projection framework, the projection matrix does not depend on the training data hence it can avoid the principal classification problems such as over-fitting, Small Sample Size (SSS),...
This paper proposes a new framework for extracting facial features based on the bag of words method, and applies it to face and facial expression recognition. Recently, the bag of words method has been successfully used in object recognition. However, for recognition problems of facial images, the orderless collection of local patches in bag of words method cannot provide strongly distinctive information...
In this work, we proposed a novel authentication system based on facial features. The proposed method is based on PCA and LDA for feature extraction, these extracted features are combined using wavelet fusion. In this work we use neural networks to classify extracted features of faces. The proposed method consists of six steps: i) Extraction of images from the database, ii) Preprocessing, iii) Feature...
Face recognition has received an increased attention from several years in the field of image analysis, pattern recognition, and computer vision. In this paper we propose a method to the problem of face recognition. The proposed method consists of two stages. In the first stage regularized linear discriminant analysis is used to extract the most significant and discriminant features and then in the...
The dimensionality reduction has always been a long lasting thorny problem on the study of facial expression recognition (FER). In this paper, we propose a novel method of facial expression recognition, which using Gaussian process latent variable models (GPLVM) for reducing the high dimensional data of facial expression images into a relatively low dimension data and using support vector machine...
In this paper, a novel framework for 3D face recognition based on depth information, is proposed. The core of our framework is Spectral Regression Kernel Discriminate Analysis (SRKDA), a method for utilizing a reproducing kernel Hubert space (RKHS) into which data points are mapped. In order to overcome facial expression variation, we first utilize curvature information projected onto the moving least-squares...
A novel combination of Trace transform and subspace method is proposed for face recognition in this paper. This method is a general framework which can be used in most tasks of images classification. We extract a number of characteristic features from facial images through taking Trace transform over a set of angular directions. By using different Trace functionals we can get different features. The...
Rough sets theory is a relatively new soft computing tool to deal with vagueness and uncertainty. It has received much attention of the researchers around the world and has expanded tremendously in the last twenty years. In this article we introduce the basic theory and character of rough sets and its applications in recent years are also pointed out. Then the theory of rough sets is introduced into...
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