> To us it's easy to pick out a dark square in the light or a > white square in the shadow, but a computer would need some > complex processing rather than just comparing pixel values. > Looking for pixel values of (120,120,120) isn't going to > find and distinguish between light and dark checkers. > David Coombes
David : Thanks you most sincerely for that explanation (below) , and please forgive my top posting an edited version of your reply , ... but I think the whole point of that link was that we _can- not_ easily tell the difference at all ( I aplogise for what an awefull mess the MicroSlop mailer does to your replies) . Anyway , Timo's initial link that Yogi resent to the list : http://images.google.de/images?q=checker+illusion&hl=de&btnG=Bilder-Suche shows just how bad our perceptions can be in extreme situations . Garry Curtis http://www.niagara.com/~studio > Not related to 3D work but image recognition, so off topic. Present image > recognition tends to work by finding similar shapes or following edge > contrast. Stick a camera on a computer and it'll capture a colour value > for > each pixel. From that it can try to guess what it's looking at by > programming shape recognition etc. In the example picture it'll see the > same > level of grey (120,120,120) for the dark squares in the light and white > squares in the shadow, and not be able to recognise there's a difference. > A > human viewer doesn't see each pixel of the image, but an overall image. > The > onlooker sees the green cylinder, the apparent shadow, the pattern of > squares, and concludes it's a 3D scene with checkerboard in shadow, so > adjusts the perception of the colours accordingly. To us it's easy to pick > out a dark square in the light or a white square in the shadow, but a > computer would need some complex processing rather than just comparing > pixel > values. Looking for pixel values of (120,120,120) isn't going to find and > distinguish between light and dark checkers. > David Coombes > [EMAIL PROTECTED]
