Search results for "Pattern Recognition"
showing 10 items of 2301 documents
Image enhancement in simple fingerprint minutiae extraction algorithm using crossing number on valley structure
2007
In fingerprint recognition system, fingerprint feature extraction algorithm requires good quality fingerprint images to produce good results. Therefore, one step in the preprocessing stage is image enhancement to improve the quality of poor fingerprint image, so the minutiae points can be detected with good results. In this paper, we present how this enhancement process in simple minutiae detection algorithm using crossing number on valley structure improves detection of true minutiae.
Simple Fingerprint Minutiae Extraction Algorithm Using Crossing Number On Valley Structure
2007
Most of the existing fingerprint extraction techniques currently available are based on ridge structure. The ridge usually has thicker structure than the valley, so that more processing time is needed to extract the ridge than extracting the valley. Taking the advantage of the thin structure of the valley, we proposed an algorithm that reduces the time needed for minutiae extraction. The algorithm was developed in Matlab environment using fingerprint images from FVC2004. In order to show the performance of the algorithm, numerical results are presented.
Fingerprint image enhancement using directional morphological filter
2005
Fingerprint images quality enhancement is a topic phase to ensure good performance in an automatic fingerprint identification system (AFIS) based on minutiae matching. In this paper a new fingerprint enhancement algorithm based on morphological filter is introduced. The algorithm is based on three steps: directional decomposition, morphological filter and composition. The performance of the proposed approach has been evaluated on two sets of images: the first one is DB3 database from Fingerprint Verification Competition (FVC) and the second one is self collected using an optical scanner
An Advanced Technique for User Identification Using Partial Fingerprint
2013
User identification is a very interesting and complex task. Invasive biometrics is based on traits uniqueness and immutability over time. In forensic field, fingerprints have always been considered an essential element for personal recognition. The traditional issue is focused on full fingerprint images matching. In this paper an advanced technique for personal recognition based on partial fingerprint is proposed. This system is based on fingerprint local analysis and micro-features, endpoints and bifurcations, extraction. The proposed approach starts from minutiae extraction from a partial fingerprint image and ends with the final matching score between fingerprint pairs. The computation o…
Single-channel EEG-based subject identification using visual stimuli
2021
Electroencephalography (EEG) signals have been recently proposed as a biometrics modality due to some inherent advantages over traditional biometric approaches. In this work, we studied the performance of individual EEG channels for the task of subject identification in the context of EEG-based biometrics using a recently proposed benchmark dataset that contains EEG recordings acquired under various visual and non-visual stimuli using a low-cost consumer-grade EEG device. Results showed that specific EEG electrodes provide consistently higher identification accuracy regardless of the feature and stimuli types used, while features based on the Mel Frequency Cepstral Coefficients (MFCC) provi…
Benchmarking Saliency Detection Methods on Multimodal Image Data
2018
Saliency detecmage processing. Most of the work is adapted to the specific application and available dataset. The present work is about a comparative analysis of saliency detection for multimodal images dataset. There were many researches on the detection of saliency on several types of images, such as multispectral, natural, 3D and so on. This work presents a first focused study on saliency detection on multimodal images. Our database was extracted from acquisitions on cultural heritage wall paintings that contain four modalities UV, IR, Visible and fluorescence. In this paper, the analysis has been performed for many methods on saliency detection. We evaluate the performance of each metho…
An Embedded Solution for Multispectral Palmprint Recognition
2018
Palmprint based identification has attracted much attention in the past decades. In some real-life applications, portable personal authentication systems with high accuracy and speed efficiency are required. This paper presents an embedded palmprint recognition solution based on the multispectral image modality. We first develop an effective recognition algorithm by using partial least squares regression, then a FPGA prototype is implemented and optimized through high-level synthesis technique. The evaluation experiments demonstrate that the proposed system can achieve a higher recognition rate at a lower running cost comparing to the reference implementations.
Hybrid surface plasma modes in circular metal-coated tapered fibers
1999
The theory of hybrid surface plasma modes in metal-coated dielectric cylinders has been developed in recent years. We demonstrate that tapered fibers with a uniform waist and a circular metal coating can be designed for an efficient excitation of the fundamental hybrid surface plasma mode. Our experimental results are in good agreement with the theory and give the basis for the development of a novel type of all-fiber polarization-independent refractive-index sensor and tunable broadband wavelength filter.
Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models.
2012
Item does not contain fulltext The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape des…
Metallothionein Gene Family in the Sea Urchin Paracentrotus lividus: Gene Structure, Differential Expression and Phylogenetic Analysis
2017
Metallothioneins (MT) are small and cysteine-rich proteins that bind metal ions such as zinc, copper, cadmium, and nickel. In order to shed some light on MT gene structure and evolution, we cloned seven Paracentrotus lividus MT genes, comparing them to Echinodermata and Chordata genes. Moreover, we performed a phylogenetic analysis of 32 MTs from different classes of echinoderms and 13 MTs from the most ancient chordates, highlighting the relationships between them. Since MTs have multiple roles in the cells, we performed RT-qPCR and in situ hybridization experiments to understand better MT functions in sea urchin embryos. Results showed that the expression of MTs is regulated throughout de…