Text’s Unsupervised Detection in Image Based on High-Frequency Wavelet Coefficients Classification
Tongcheng Huang · JOURNAL OF HUNAN AGRICULTURAL UNIVERSITY · 2006
Text localization and its recognition in images was important for searching information in digital photo archives,video databases and web sites.However,since it was often printed against a complex background,text was often difficult to be detected.A robust text localization approach was proposed,which could automatically detect horizontally aligned text with different sizes,fonts,colors and languages.First,a wavelet transform was applied to the image and the distribution of high-frequency wavelet coefficients would discrete characterize text and non-text areas.Then,the K-means algorithm was used to classify text areas in the image.The detected text areas under went a projection analysis before refinement their localization.Finally,a binary segmented text image was generated,to be used as input to an OCR engine.The detection performance of the approach was proved experimental demonstration.