Extraction of Color Image Texts Combining Wavelet Interpolation and K-means
Murong Jiang · Computer Technology and Development · 2013
The text extraction and recognition of color images is the research focus in the field of artificial intelligence and pattern recognition.In order to solve the problems of text recognition that the characters in color images are too small to see clearly and the color of the characters is similar as the complex background or the characters are arranged irregularly,use the method which combines the wavelet interpolation and K-means cluster to extract the color texts.First,choose the region including the color texts,then employ the wavelet interpolation to enlarge the color image,use K-means method to cluster the color to obtain a single background image,then change this image into the binary image and segment the text.At last,the trained BP neural network is used for the character recognition.Some experiments show that this method can process the most color text extraction easily,and more efficiently for recognizing the text with the lower contrast and complex background.