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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32710


    Title: 植基於質感圖樣之自動化人機區分機制
    A CAPTCHA Mechanism Based on Textured Patterns
    Authors: 張繼志
    Chi-Chih Chang
    Contributors: 廖文宏
    Wen-Hung Liao
    張繼志
    Chi-Chih Chang
    Keywords: 人機辨識
    質感圖樣
    CAPTCHA
    Turning Test
    Texture
    Visual Pattern
    Date: 2004
    Issue Date: 2009-09-17 14:06:36 (UTC+8)
    Abstract: 隨著科技的進步與資訊科學的發展，大量的資訊處理自動化逐漸取代傳統人工技術，然而不恰當地使用自動化技術，卻可能危害人類的權益與空間。為避免過度濫用機器自動化對人類所造成的災害，本研究根據不同的適用情境，分別提出以靜態及動態圖型為基礎的人機區分方法，透過簡單的影像處理技術，產生機器難以分析但人類能夠易於判別的人機辨識影像。並且由認知的角度，設計實驗進一步探討人類視覺優勢以及接受度，作為影像產生時的標準。最後，提出人機區分技術與應用情境整合實作的方法，以觀實效。
    The idea of using a computer program to distinguish humans from machines, sometimes referred to as the “Reverse Turing Test”, has emerged only quite recently. The term CAPTCHA, which stands for “Completely Automated Public Turing Test to Tell Computers and Humans Apart", is defined as:
    “a program that can generate and grade tests that:
    □ Most human can pass
    but
    □ Current computer program can’t pass! “
    In this thesis, a texture-image based approach is developed to encode text information in such a way that machine vision algorithms will experience significant difficulties while human can extract the embedded text effortlessly. Both static images and dynamic sequences will be explored. It is anticipated that the cost of storing, and subsequently decoding information from such visual patterns will be prohibitedly high, both in terms of time and space complexity. To validate the postulation, fundamental principles of the human cognitive process will be examined. Experiments will also be carried out to gather user feedback and investigate the limitations of human visual systems. Finally, several application scenarios that call for the integration of a CAPTCHA will be identified and discussed.
    Reference: 【1】Berners-Lee, T., Hendler, J. and Lassila, O. (2001). The Semantic Web. Scientific American.
    【2】Turing, A. (1950). Computing machinery and intelligence, artificial intelligence.
    【3】Ahn, L von., Blum, M., Hopper, N. J., and Langford, J. (2003). CAPTCHA: Telling Humans and Computers Apart (Automatically). Advances in Cryptology, Eurocrypt `03, volume 2656 of Lecture Notes in Computer Science, 294–311.
    【4】Mori, G. and Malik, J. (2003). Recognizing objects in adversarial clutter: Breaking a visual CAPTCHA. In Proceedings of the Conference on Computer Vision and Pattern Recognition,. Vol. I, pp.134-141, Madison, USA.
    【5】Kochanski, G., Lopresti, D., and Shih, C. (2002). A Reverse Turing Test Using Speech. Seventh International Conference on Spoken Language Processing, 16-20.
    【6】Julesz, B. and Miller, J.E. (1962). Automatic stereoscopic presentation of functions of two variables. Bell System Technical Journal, 41: 663-676.
    【7】Goldstein, E. B. (1999). Sensation and Perception, Fifth Edition, Brooks/Cole Publishing Company.
    【8】Kanizsa, G.. (1955). Margini quasi-percettivi in campi con stimolazione omogenea. Rivista di psicologia, 49, 7-30.
    【9】Bradley, D. R., and Petry, H. M. (1977). Organizational determinants of subjective contour: The subjective Necker cube. American Journal of Psychology, 90, 253-262.
    【10】Williams, L. R. and Jacobs, D. W. (1997). Stochastic Completion Fields: A Neural odel of Illusory Contour Shape and Salience, Neural Computation, Vol. 9, No. 4, pp. 837-858.
    【11】Julesz, B. (1962). Visual pattern discrimination. IRE Trans Inf Theory, IT-8:84-92.
    【12】Julesz, B. (1975). Experiments on the visual perception of texture. Scientific American, 232, 34-43.
    【13】Julesz, B. Textons. (1981). the elements of texture perception and their interactions. Nature, London, 290, 91-97.
    【14】Regan, D. (1986). Luminance contrast: Vernier discrimination. Spatial Vision, 1, 305-318.
    【15】Newsome, W. T., Britten, K. H., and Movshon, J. A. (1989). Neuronal correlates of a perceptual decision. Nature, 341, 52-54.
    【16】Gonzalez, R. C. and Woods, R. E. (2001). Digital Image Processing Second Edition. Prentice-Hall, Inc.
    【17】Forsyth, D. A.,and Ponce, J. (2003). Computer Vision: A Modern Approach. Prentice-Hall, Inc.
    【18】Myers, A. and Hansen, C. (1997). Experimental Psychology. Brooks/Cole Publishing Company.
    【19】Duda, R. O., Hart, P. E., and Stork, D. G... (2001). Pattern Classification, Second Edition. John Wiley & Sons, Inc.
    【20】Liao, W. H., Chang, C.C. (2004). Embedding Information within Dynamic Visual Patterns. The 2004 IEEE International Conference On Multimedia And Expo.
    【21】王文中，(1999)，「統計學與Excel資料分析之實習應用」，博碩文化。
    【22】李江山、孫慶文、陳一平、陳建中、黃淑麗、黃榮村、葉素玲、襲充文、櫻井正二郎，(2002)，「視覺與認知–視覺知覺與視覺運動系統」，遠流。
    【23】洪蘭、曾志朗譯，(1997)，「心理學實驗研究法」，遠流。
    Description: 碩士
    國立政治大學
    資訊科學學系
    91753014
    93
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0917530141
    Data Type: thesis
    Appears in Collections:[Department of Computer Science ] Theses

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