Modified Method of Document Text Extraction from Document Images Using Haar DWT

This paper extends the technique used for Document Text Extraction from Images using 2-D Haar Wavelet. The discrete wavelet transform is a very useful tool for signal analysis and image processing, especially in multi-resolution representation. It can decompose signal into different components in the frequency domain. Two-dimensional discrete wavelet transform (2-D DWT) decomposes an input image into four sub-bands, one average component (LL) and three detail components (LH, HL, HH). The multiresolution of 2-D DWT has been employed to detect edges of an original image. We select an appropriate threshold value and preliminarily remove the non-text edges in the detail component sub-bands. Then we use the logical AND operator to further removes the non-text regions. Another idea of removing the large size area in the image is merged with this idea to eliminate the non-text region from Document Images. Keywords—Average component, Detail components, Document text, DWT, Multi-resolution of 2-D DWT, Non-Text Edges, Sub-band images, Text extraction, 2-D Haar Wavelet ——————————  ——————————