Patent ID: 7436994
Filing Date: 2008-10-14
Classification: G06K

Abstract:
1. A system of using a neural network to distinguish text and pictures in an image, a set of training data being used to train the neural network in advance to generate text recognition knowledge, the system comprising: an image block division module, which extracts gray-level image data of the image and divides the gray-level image data into a plurality of image blocks, each of which contains a plurality of block columns each of which is made of a plurality of continuous pixels; a neural network module, which uses the text recognition knowledge to process the continuous pixels of the block column, generating a text faith value for each of the pixels and obtaining a greatest text faith value; and a text determination module, which compares a text threshold with the greatest text faith value to determine the status of the image block, wherein the training data include photo-to-text data, white-to-text data, text-to-photo/white data, text-to-text data, no text data, data of text with more than one edge, and data of text with halftoning noise.