W niniejszym artykule przedstawiono wpływ reprezentacji kolorów na wyniki segmentacji metodami rozrostu obszarów oraz metodą quadtree. Pod uwagę wzięto popularnie stosowane przestrzenie kolorów, takie jak RGB, HSV, CIEL*a*b. Przedstawiono matematyczną miarę jakości segmentacji oraz skonfrontowano ją z subiektywnymi odczuciami człowieka. Przy opracowaniu wyników użyto zestawów obrazów z kolekcji COREL oraz zdjęć lotniczych użytych w serwisach Google.
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This paper describes influence of color space to the results of image segmentation by watershed and quadtree algorithms. The most popular color space like RGB, HSV and CIEL*a*b was analyzed. The mathematical measure of segmentation quality was presented and contrasted with the subjective human feelings. Sets of images from COREL collection and aerial images from Google were used in experiments.
The presented paper is concerned with feature space derivation through feature selection. The selection is performed on results of kernel Principal Component Analysis (kPCA) of input data samples. Several criteria that drive feature selection process are introduced and their performance is assessed and compared against the reference approach, which is a combination of kPCA and most expressive feature reordering based on the Fisher linear discriminant criterion. It has been shown that some of the proposed modifications result in generating feature spaces with noticeably better (at the level of approximately 4%) class discrimination properties.
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The authors in this publication present the concept of control system for the console operator to manage mobile robot platform and its components. Implemented functionality provides the ability to set the robot in different modes. The operator can control the state of robot using simple commands, and is also able to carry more complex tasks. The applied layered software architecture and Object-oriented programming (OOP) allows for easy management of software, maintenance, reusability and its further development.
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Robotic vehicles autonomy is the subject of many researches performed by various institutions. There is growing tendency to conduct research in the field of autonomous mobile units, unmanned vehicles and robots moving without operator supervision. Authors of this article presents the concept of the modularized subsystem implementing the functionality of the mobile platform navigation in an unknown environment. The concept has been implemented in the real mobile robot.
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In this paper a double source images fusion algorithm is presented. Its task is to enhance temperature feature of objects located on the scene. Presented solution is design to be executed in real-time environment. It consists of three stages: in the first part the differences between acquired double source images are examined in order to determine their intersection. Then for each analysed image the contours of all objects located on the scene are determined. This operation is essential to solve disparition issue. In the last stage, based on determined contours and their match coefficient the images are fused. The enhanced temperature feature is displayed on one image acquired from day-light camera.
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