Showing papers in "Pattern Recognition in 2005"

TL;DR: This paper surveys and summarizes previous works that investigated the clustering of time series data in various application domains, including general-purpose clustering algorithms commonly used in time series clustering studies.

TL;DR: Study of the performance of different normalization techniques and fusion rules in the context of a multimodal biometric system based on the face, fingerprint and hand-geometry traits of a user found that the application of min-max, z-score, and tanh normalization schemes followed by a simple sum of scores fusion method results in better recognition performance compared to other methods.

TL;DR: A hybrid learning algorithm is proposed which uses the differential evolutionary algorithm to select the input weights and Moore-Penrose (MP) generalized inverse to analytically determine the output weights.

TL;DR: The tests show that the extracted features are independent of sensor location, invariant to the individual's state of anxiety, and unique to an individual.

TL;DR: Experimental results on Concordia University CENPARMI database of handwritten Arabic numerals and Yale face database show that recognition rate is far higher than that of the algorithm adopting single feature or the existing fusion algorithm.

TL;DR: The use of combined neural network model to guide model selection for classification of electrocardiogram (ECG) beats achieved accuracy rates which were higher than that of the stand-alone neuralnetwork model.

TL;DR: 2DLDA provides a sequentially optimal image compression mechanism, making the discriminant information compact into the up-left corner of the image, and suggests a feature selection strategy to select the most discriminative features from the corner.

TL;DR: A new thresholding technique is introduced which processes thresholds as type II fuzzy sets and a new measure of ultrafuzziness is also introduced and experimental results using laser cladding images are provided.

TL;DR: This method is efficient as it only uses simple operations such as parity check and comparison between average intensities and effective because the detection is based on a hierarchical structure so that the accuracy of tamper localization can be ensured.

TL;DR: The goal of this paper is to introduce a certain number of papers related with grammatical inference, some of which are essential and should constitute a common background to research in the area, whereas others are specialized on particular problems or techniques, but can be of great help on specific tasks.

TL;DR: This work presents an approach that uses localized secondary features derived from relative minutiae information that is directly applicable to existing databases and balances the tradeoffs between maximizing the number of matches and minimizing total feature distance between query and reference fingerprints.

TL;DR: An efficient two-dimensional-to-three-dimensional integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination and the synthesized virtual faces significantly improve the accuracy of face recognition with changing PIE.

TL;DR: The method of wavelet preprocessed golden image subtraction (WGIS) has been developed for defect detection on patterned fabric or repetitive patterned texture and it can be concluded that the WGIS method provides the best detection result.

TL;DR: This paper proposes a new colour invariant image representation based on an existing grey-scale image enhancement technique: histogram equalisation and applies the method to an image indexing application and shows that the method out performs all previous invariant representations.

TL;DR: Experiments on the ORL and the UMIST face databases show that the new scheme outperforms the PCA and the conventional PCA+FLD schemes, not only in its computational efficiency, but also in its performance for the task of face recognition.

TL;DR: A new secret sharing scheme capable of protecting image data coded with B bits per pixel is introduced and analyzed in this paper, which allows for cost-effective cryptographic image processing of B-bit images over the Internet.

TL;DR: The experiments conducted on a bi-class problem show that the proposed methodology can adequately choose the SVM hyper-parameters using the empirical error criterion and it turns out that the criterion produces a less complex model with fewer support vectors.

TL;DR: The proposed scheme is shown to outperform significantly the fusion approach without considering quality signals and a relative improvement of approximately 20% is obtained on the publicly available MCYT bimodal database.

TL;DR: This paper characterize user's identity through the simultaneous use of three major palmprint representations and achieve better performance than either one individually and proposes product of sum rule which achieves betterperformance than any other fixed combination rules.

TL;DR: A novel shape similarity retrieval algorithm that can be used to match and recognize 2D objects using a new multi-resolution polygonal shape descriptor that is invariant to scale, rotation and translation.

TL;DR: It is shown that the use of an average deformation model leads to an improvement in the alignment between impressions originating from the same finger.

TL;DR: This article presents an overview of Probabilistic Automata (PA) and discrete Hidden Markov Models (HMMs), and aims at clarifying the links between them, and presents several learning models, which formalize the problem of PA induction or, equivalently, theproblem of HMM topology induction and parameter estimation.

TL;DR: Experiments show that the proposed method for assisting in human identification using dental radiographs is effective for dental image classification and teeth segmentation, provides good results for separating each tooth into crown and root, and provides a good tool for human identification.

TL;DR: A system for automating that process by identifying people from dental X-ray images by retrieves the best matches from an antemortem (AM) database and developed a new method for teeth separation based on integral projection.

TL;DR: This work proposes a novel adaptive approach for character segmentation and feature vector extraction from seriously degraded images that can detect fragmented, overlapped, or connected character and adaptively apply for one of three algorithms without manual fine-tuning.

TL;DR: A novel approach to the problem of automatic off-line signature verification and forgery detection based on fuzzy modeling that employs the Takagi-Sugeno (TS) model is proposed, finding that TS model with multiple rules is better thanTS model with single rule for detecting three types of forgeries.

TL;DR: The comprehensive experiments completed on ORL, Yale, and CNU (Chungbuk National University) face databases show improved classification rates and reduced sensitivity to variations between face images caused by changes in illumination and viewing directions.

TL;DR: A novel illumination compensation algorithm, which can compensate for the uneven illuminations on human faces and reconstruct face images in normal lighting conditions and eliminate the influence of uneven illumination while retaining the shape information about a human face is proposed.

TL;DR: Experimental results on classifying data of a surface inspection task and data sets from the UCI repository show that Bayesian network classifiers are competitive with selective k-NN classifiers concerning classification accuracy.

TL;DR: A new method using Gabor filters for character recognition in gray-scale images is proposed and has excellent performance on both low-quality machine-printed character recognition and cursive handwritten character recognition.