Using artificial neural network for the calculation of iterated function system codes

Alex W H Lee, L. M. Cheng

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    Abstract

    Iterated Function system (IFS) is one of the most useful methodology in fractal transformation. The collage theorem states that image reconstruction as well image compression can be performed using IFS, but the main disadvantage of this algorithm is computational intensive during extracting suitable attractors to represent the target image. In this paper, artificial neural network is investigated as an alternative tool for IFS attractors' calculation to extract the corresponding image segment. The advantages of the use of ANN are fast, low cost and small once the image segment set has been identified. This paper indicates that ANN is a practical alternative approach.
    Original languageEnglish
    Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
    PublisherIEEE
    Pages4038-4043
    Volume6
    Publication statusPublished - 1994
    EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
    Duration: 27 Jun 199429 Jun 1994

    Publication series

    Name
    Volume6

    Conference

    ConferenceProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
    CityOrlando, FL, USA
    Period27/06/9429/06/94

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