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Detection and Recognition of Selected Class Railway Signs

Mikrut S., Mikrut Z., Moskal A., Pastucha E.

Image Processing & Communications

2014

Vol. 19, no. 2-3

83--96

The paper aims at presentation of results of research on detection and recognition of selected class railway signs (W11p). When conducting the research, the authors have proposed their own algorithm, which achieved about 90% effectiveness at detecting W11p signs and 98% effectiveness at classifying them. The processes of localisation, segmentation and recognition of W11p signs were considerably simplified thanks to the application of backpropagation neural network. The authors believe that two non-standard methods related to the use of the network deserve attention: the application of an interactive method of generating the training set, owing to which also pixels highly diversified in terms of their colours could be included, and the use of a full spectrum of neural network responses, which made it possible to accomplish a feedback. It consisted in an automatic adjusting of the network responses’ threshold to the results of segmentation and recognition.

The Topological Structures of Membrane Computing

Giavitto J-L., Michel O.

Fundamenta Informaticae

2002

Vol. 49, nr 1-3

123-145

In its initial presentation, the P system formalism describes the topology of the membranes as a set of nested regions. In this paper, we present an algebraic structure developped in combinatorial topology that can be used to describe finer adjacency relationships between membranes. Using an appropriate abstract setting, this technical device enables us to reformulate also the computation within a membrane and proposes a unified view on several computational mechanisms initially inspired by biological processes. These theoretical tools are instantiated in MGS, an experimental programming language handling various types of membrane structures in a homogeneous and uniform syntax.