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THE PROBLEM OF IMAGE RECOGNITION
Image Recognition and Association Humans are very good at image recognition. The moment we see a picture of a monkey, we connect it to the word "MONKEY". We can recognise handwriting, photographs, paintings and other visual media with a high degree of speed and accuracy. Image recognition, though a trivial task for us, can be very difficult for computer programs. For example, it is obvious to us that all the images below represent the same object, the letter B: However, even if a program is aware that an image contains letters somewhere, how is it to infer which way they are oriented? Also, the given images could be damaged in some way (smudged, blurred, incomplete or discoloured). Even the most advanced image recognition programs available have problems with this. Most commercial character-recognition programs require the user to position the images beforehand in a set way. Undamaged and damaged versions of the letter B Computer programs with the ability to recognise images are very useful. They are used by the police to associate fingerprints collected from crime scenes to known criminals, or for identifying criminals from photographs. Banks use them to verify signatures on important documents. Some security systems match employees faces with the photographs on their identity cards. Electronic book readers for the visually impaired recognise words printed in books and read them out aloud. In fact, such programs are applicable in any area in which repetitive and fast classification of information is required. Recognition is not limited to images. Voice recognition software is available that enables the user to dictate documents to a computer, which types out words as it hears them. Some security systems have voice locks that open only if authorised personnel speak their own passwords. Methods of image recognition Modern methods of image recognition utilize mathematical methods such as Wavelet Analysis, Fast Fourier Transforms and Neural Networks.
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