Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: low-level features

Sortuj według:

Ogranicz wyniki do:

Analysis of possible system-level hardware implementation of the selected shape description algorithms

Frejlichowski D.

Journal of Theoretical and Applied Computer Science

2012

Vol. 6, nr 4

51-58

This paper is devoted to the problem of the hardware implementation of selected shape description algorithms. The properties and complexity of particular methods are discussed in order to find those that are most applicable to a direct hardware implementation. Thus, the complexity of both the approaches and the processed data should be minimised. In this paper the properties of the Roundness, X/Y Feret, Point Distance Histogram, UNL, UNL-Fourier and Fourier Descriptors methods were investigated. Two aspects were analysed — the efficiency of an exemplary practical shape analysis application and the time consumption of the implemented algorithms.

Current challenges in content based image retrieval by means of low-level feature combining

Forczmański P., Frejlichowski D.

Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica

2010

Vol. 10, no. 1

41--49

The aim of this paper is to discuss a fusion of the two most popular low-level image features - colour and shape - in the aspect of content-based image retrieval. By combining them we can achieve much higher accuracy in various areas, e.g. pattern recognition, object representation, image retrieval. To achieve such a goal two general strategies (sequential and parallel) for joining elementary queries were proposed. Usually they are employed to construct a processing structure, where each image is being decomposed into regions, based on shapes with some characteristic properties - colour and its distribution. In the paper we provide an analysis of this proposition as well as the exemplary results of application in the Content Based Image Retrieval problem. The original contribution of the presented work is related to different fusions of several shape and colour descriptors (standard and non-standard ones) and joining them into parallel or sequential structures giving considerable improvements in content-based image retrieval. The novelty is based on the fact that many existing methods (even complex ones) work in single domain (shape or colour), while the proposed approach joins features from different areas.