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Metoda wektoryzacji obrazu sceny dla autonomicznego robota

Śmigielski P.

Technical Issues

2015

nr 4

32--38

The aim of the studies was to design, implement and test the algorithm for vectorization of the scene, which is analyzed by an autonomous robot. The vectorization is the process of extraction of the contours of the objects located in the image taken by a camera. The result is stored in a computer's (robot's) memory as a sequence of points in euclidean space marking the examined objects' corners. During the tests, various images were used. Each one was previously pre-processed in a different way in order to reveal and highlight the contours of the objects. The vectorization process is divided into three steps which are described in detail in this article.

Genetic algorithm for clustering, finding the number of clusters

Śmigielski P.

Schedae Informaticae

2011

Vol. 20

101-113

In this paper a genetic algorithm for clustering is proposed. The algorithm is based on the variable length chromosomes and the notion of local points density in the clustered set. Its role is to identify the number of clusters in the clustered set and to partition this set into particular clusters. The tests were conducted for two different sets of two dimensional data. The algorithm performed well in both cases. The tests presented the ability of the algorithm to partition the subsets combined with the thin dense area into separate clusters.