scholarly journals Features Extraction for Pollen Recognition Using Gabor Filters

2018 ◽  
Vol 1 (2) ◽  
pp. 86
Author(s):  
Dimitar Nikolov Nikolov ◽  
Diana Dimitrova Tsankova
Keyword(s):  
Filter Bank ◽  
Recognition System ◽  
Gabor Filters ◽  
Features Extraction ◽  
Botanical Origin ◽  
Biologically Inspired ◽  
Microscope Images ◽  
European Pollen Database ◽  
Components Analysis

The aim of the article is to investigate the features extraction from microscope images of pollens for a classification of honey on the base of its botanical origin. A filter-bank of Gabor filters (as a biologically inspired recognition system) is used to obtain features, which are then post-processed using normalization, down-sampling (by bicubic interpolation), and principal components analysis (PCA). PCA is used for reducing the features size and a proper visualization of the features extraction results. Microscope images from the European pollen database, including pollen images of linden, acacia, lavender, rapeseed, and thistle, are used to illustrate capabilities of the proposed features extraction approach. The performance of the proposed algorithm is evaluated by simulations in MATLAB environment.

ALGORITHMS FOR FINGERPRINT CLASSIFICATION

2021 ◽  
Vol 335 (1) ◽  
pp. 39-44
Author(s):  
D. Lebedev ◽  
A. Abzhalilova
Keyword(s):  
Neural Network ◽  
Gabor Filter ◽  
Recognition System ◽  
Personal Identification ◽  
External Object ◽  
Biometric Identification ◽  
Fingerprint Classification ◽  
Combined Application ◽  
Traditional Approaches

Currently, biometric methods of personality are becoming more and more relevant recognition technology. The advantage of biometric identification systems, in comparison with traditional approaches, lies in the fact that not an external object belonging to a person is identified, but the person himself. The most widespread technology of personal identification by fingerprints, which is based on the uniqueness for each person of the pattern of papillary patterns. In recent years, many algorithms and models have appeared to improve the accuracy of the recognition system. The modern algorithms (methods) for the classification of fingerprints are analyzed. Algorithms for the classification of fingerprint images by the types of fingerprints based on the Gabor filter, wavelet - Haar, Daubechies transforms and multilayer neural network are proposed. Numerical and results of the proposed experiments of algorithms are carried out. It is shown that the use of an algorithm based on the combined application of the Gabor filter, a five-level wavelet-Daubechies transform and a multilayer neural network makes it possible to effectively classify fingerprints.

scholarly journals The Methodical Approach to Integrated Multi-criteria Assessment of Intellectual Capital

2021 ◽  
Vol 5 (520) ◽  
pp. 281-288
Author(s):  
O. V. Stepanova ◽  
Keyword(s):  
Utility Function ◽  
Intellectual Capital ◽  
Utility Theory ◽  
Factors Affecting ◽  
Management By Objectives ◽  
Methodical Approach ◽  
Components Analysis ◽  
Capital Development ◽  
Integral Indicator

The article is aimed at developing scientific-methodological recommendations for the integrated multi-criteria assessment of intellectual capital. Achieving this goal requires solving the following tasks: analysis of the theoretical principles of intellectual capital; analysis of intellectual capital components; analysis of methods for assessment of intellectual capital; development of a multi-criteria model of integrated assessment of intellectual capital on the basis of program-target approach and utility theory. In line with the conception of management by objectives, as well as in accordance with both the systemic and the program-target approaches, the objectives of enterprise are formulated taking into account the growth, renewal and efficient use of intellectual capital. Based on the analysis of available publications, a classification of factors affecting intellectual capital is compiled. Using the structure of intellectual capital and graph theory, the «tree of purposes» of intellectual capital is built, which represents an unoriented, bound graph, the verticals (nodes) of which are purposes, and the ribs (arcs) are the links between them. A system of criteria – indicators that affect the achievement of the objectives is formulated. As a criterion for optimality of achieving the objective, it is proposed to use the multi-criteria utility function. It is noted that in order to assess intellectual capital, it is advisable to use the additive utility function, which makes it possible to compute the integral indicator of intellectual capital. This, in turn, allows to analyze the growth, renewal and efficiency of the intellectual capital of enterprise over a number of years, as well as compare enterprises with each other.

scholarly journals Handwritten tifinagh character recognition using simple geometric shapes and graphs

2019 ◽  
Vol 13 (2) ◽  
pp. 598
Author(s):  
Youssef Ouadid ◽  
Abderrahmane Elbalaoui ◽  
Mehdi Boutaounte ◽  
Mohamed Fakir ◽  
Brahim Minaoui
Keyword(s):  
Character Recognition ◽  
Graph Matching ◽  
Recognition Rate ◽  
Recognition System ◽  
Features Extraction ◽  
Experimental Results ◽  
Feature Points ◽  
Matching Method ◽  
Extraction Algorithm ◽  
Novel Algorithm

<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

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