Search results for "algorithm"
showing 10 items of 4887 documents
Fast Fingerprints Classification only using the Directional Image
2007
The classification phase is an important step of an automatic fingerprint identification system, where the goal is to restrict only to a subset of the whole database the search time. The proposed system classifies fingerprint images in four classes using only directional image information. This approach, unlike the literature approaches, uses the acquired fingerprint image without enhancement phases application. The system extracts only directional image and uses three concurrent decisional modules to classify the fingerprint. The proposed system has a high classification speed and a very low computational cost. The experimental results show a classification rate of 87.27%.
Blood vessels and feature points detection on retinal images
2009
In this paper we present a method for the automatic extraction of blood vessels from retinal images, while capturing points of intersection/overlap and endpoints of the vascular tree. The algorithm performance is evaluated through a comparison with handmade segmented images available on the STARE project database (STructured Analysis of the REtina). The algorithm is performed on the green channel of the RGB triad. The green channel can be used to represent the illumination component. The matched filter is used to enhance vessels w.r.t. the background. The separation between vessels and background is accomplished by a threshold operator based on gaussian probability density function. The len…
Clifford Algebra based Edge Detector for Color Images
2012
Edge detection is one of the most used methods for feature extraction in computer vision applications. Feature extraction is traditionally founded on pattern recognition methods exploiting the basic concepts of convolution and Fourier transform. For color image edge detection the traditional methods used for gray-scale images are usually extended and applied to the three color channels separately. This leads to increased computational requirements and long execution times. In this paper we propose a new, enhanced version of an edge detection algorithm that treats color value triples as vectors and exploits the geometric product of vectors defined in the Clifford algebra framework to extend …
Simulated Annealing Technique for Fast Learning of SOM Networks
2011
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensi…
A New Embedded Coprocessor for Clifford Algebra based Software Intensive Systems
2011
Computer graphics applications require efficient tools to model geometric objects and their transformations. Clifford algebra (also known as geometric algebra) is receiving a growing attention in many research fields, such as computer graphics, machine vision and robotics, as a new, interesting computational paradigm that offers a natural and intuitive way to perform geometric calculations. At the same time, compute-intensive graphics algorithms require the execution of million Clifford operations. Clifford algebra based software intensive systems need therefore the support of specialized hardware architectures capable of accelerating Clifford operations execution. In this paper the archite…
Robust Data Gathering for Wireless Sensor Networks
2006
2005 13th IEEE International Conference on Networks jointly held with the 2005 7th IEEE Malaysia International Conference on Communications, Proceedings Volume 1, 2005, Article number 1635527, Pages 469-474 2005 13th IEEE International Conference on Networks jointly held with the 2005 7th IEEE Malaysia International Conference on Communications; Kuala Lumpur; Malaysia; 16 November 2005 through 18 November 2005; Category number05EX1235; Code 69262 Robust data gathering for wireless sensor networks (Conference Paper) Ortolani, M. , Gatani, L. , Lo Re, G. Dipartimento di Ingegneria Informatica, Università degli Studi di Palermo, Viale delle Scienze Parco d'Orleans, 90128 Palermo, Italy View re…
A Novel Time Series Kernel for Sequences Generated by LTI Systems
2017
The recent introduction of Hankelets to describe time series relies on the assumption that the time series has been generated by a vector autoregressive model (VAR) of order p. The success of Hankelet-based time series representations prevalently in nearest neighbor classifiers poses questions about if and how this representation can be used in kernel machines without the usual adoption of mid-level representations (such as codebook-based representations). It is also of interest to investigate how this representation relates to probabilistic approaches for time series modeling, and which characteristics of the VAR model a Hankelet can capture. This paper aims at filling these gaps by: deriv…
A MOBILE ROBOT FOR TRANSPORT APPLICATIONS IN HOSPITAL DOMAIN WITH SAFE HUMAN DETECTION ALGORITHM
2009
We have been developing a MKR (Muratec Keio Robot), an autonomous omni-directional mobile transfer robot system for hospital applications. This robot has a wagon truck to transfer luggage, important specimens and other materials. This study proposes a safe obstacle collision avoidance technique that includes a human detection algorithm for omni directional mobile robots that realizes a safe movement technology. The robot can distinguish people from others obstacles with human detection algorithm. The robot evades to people more safely by considering its relative position and velocity with respect to them. Some experiments in a hospital were carried out to verify the performance of the human…
A New Class of Searchable and Provably Highly Compressible String Transformations
2019
The Burrows-Wheeler Transform is a string transformation that plays a fundamental role for the design of self-indexing compressed data structures. Over the years, researchers have successfully extended this transformation outside the domains of strings. However, efforts to find non-trivial alternatives of the original, now 25 years old, Burrows-Wheeler string transformation have met limited success. In this paper we bring new lymph to this area by introducing a whole new family of transformations that have all the "myriad virtues" of the BWT: they can be computed and inverted in linear time, they produce provably highly compressible strings, and they support linear time pattern search direc…
A MAS metamodel-driven approach to process fragments selection
2009
The construction of ad-hoc design processes is more and more required today. In this paper we present our approach for the construction of a new design process following the Situational Method Engineering paradigm. We mainly focus on the selection and assembly activities on the base of what we consider a key element in agent design processes: the MAS metamodel. The paper presents an algorithm establishing a priority order in the realization (instantiation) of MAS metamodel elements by the fragments that will compose the new process.