The recently initiated and rapidly developing research field of 'human interactive proofs' (HIPs) and its implications for the document image analysis (DIA) research field are described. Over the last five years, efforts to defend Web services against abuse by programs ('bots') have led to a new family of security protocols able to distinguish between human and machine users. AltaVista pioneered this technology in 1997 [Bro01, LBBB01]. By the summer of 2000, Yahoo! and PayPal were using similar methods. In the Fall of 2000, Prof. Manuel Blum of Carnegie-Mellon University and his team, stimulated by Udi Manber of Yahoo!, were studying these and related problems [BAL00]. Soon thereafter a collaboration between the University of California at Berkeley and the Palo Alto Research Center (PARC) built a tool based on systematically generated image degradations [CBF01]. In January 2002, Prof. Blum and the present authors ran the first workshop (at PARC) on HIPs, defined broadly as a class of challenge/response protocols which allow a human to authenticate herself as a member of a given group-e.g. human (vs. machine), herself (vs. anyone else), an adult (vs. a child), etc. All commercial uses of HIPs known to us exploit the gap in ability between human and machine vision systems in reading images of machine printed text. Many technical issues that have been systematically studied by the DIA community are relevant to the HIP research program. This paper describes the evolution of HIP R&D, applications of HIPs now and on the horizon, highlights of the first HIP workshop, and proposals for a DIA research agenda to advance the state of the art of HIPs.
We exploit the gap in ability between human and machine vision systems to craft a family of automatic challenges that tell human and machine users apart via graphical interfaces including
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