PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Righi M., D'Acunto M., Salvetti O. PRIAR using a graph segmentation method. In: IMTA 2015 - 5th International Workshop on Image Mining. Theory and Applications (Berlin, 11-14 March 2015). Proceedings, pp. 46 - 51. Igor Gurevich, Heinrich Niemann, Ovidio Salvetti and Bernd Radig (eds.). SCITEPRESS Digital Library, 2015.
 
 
Abstract
(English)
Recently, we have suggested a simple and general-purpose method able to combine high-resolution analysis with the classification and identification of components of microscopy imaging. The method named PRIAR (Pattern Recognition Image Augumented Resolution) is a tool developed by the authors that gives the possibility to enhance spatial and photometric resolution of low-res images. The implemented algorithm follows the scheme: 1) image classification; 2) blind super-resolution on single frame; 3) pattern-analysis; 4) reconstruction of the discovered pattern. In this paper, we suggest some improvements of the PRIAR algorithm, in particular, the definition of a segmentation method which is based on homomorphism between a processed image and a graph describing the image itself, able to identify object of interest in complex patterns. The case study is the identification of organs inside biological cells acquired with Atomic Force Microscopy Technique.
Subject Pattern Recognition
Image Analysis
Image Segmentation
Boundary Detection
Graph Partitioning Algorithm
I.5 PATTERN RECOGNITION
I.5.2 PATTERN RECOGNITION. Design Methodology
F.2.2 Nonnumerical Algorithms and Problems
I.4 IMAGE PROCESSING AND COMPUTER VISION
I.4.6 IMAGE PROCESSING AND COMPUTER VISION. Segmentation
G.2.2 DISCRETE MATHEMATICS. Graph Theory
I.2.8 ARTIFICIAL INTELLIGENCE. Problem Solving, Control Methods, and Search


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