Search results for " Directional Map"

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An Embedded Fingerprints Classification System based on Weightless Neural Networks

2009

Automatic fingerprint classification provides an important indexing scheme to facilitate efficient matching in large-scale fingerprint databases in Automatic Fingerprint Identification Systems (AFISs). The paper presents a new fast fingerprint classification module implementing on embedded Weightless Neural Network (RAM-based neural network). The proposed WNN architecture uses directional maps to classify fingerprint images in the five NIST classes (Left Loop, Right Loop, Whorl, Arch and Tented Arch) without anyone enhancement phase. Starting from the directional map, the WNN architecture computes the fingerprint classification rate. The proposed architecture is implemented on Celoxica RC20…

Embedded Fingerprint Classification Weightless Neural Network RAM based Neural Networks Directional Map FPGA.
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A Fast Multiresolution Approach Useful for Retinal Image Segmentation

2018

Retinal diseases such as retinopathy of prematurity (ROP), diabetic and hypertensive retinopathy present several deformities of fundus oculi which can be analyzed both during screening and monitoring such as the increase of tortuosity, lesions of tissues, exudates and hemorrhages. In particular, one of the first morphological changes of vessel structures is the increase of tortuosity. The aim of this work is the enhancement and the detection of the principal characteristics in retinal image by exploiting a non-supervised and automated methodology. With respect to the well-known image analysis through Gabor or Gaussian filters, our approach uses a filter bank that resembles the “à trous” wav…

0301 basic medicine03 medical and health sciences030104 developmental biologySettore INF/01 - Informaticabusiness.industryComputer scienceRetinal image segmentationComputer visionArtificial intelligencebusinessElliptical Gaussian filters Directional Map Retinal Vessel Fundus OculiProceedings of the 7th International Conference on Pattern Recognition Applications and Methods
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