Effective reconstruction of compressed scanned document using advanced video codec

The video compression is used to reduce the size of the video files. The MPEG files are compressed then the fine details of video are lost their originality due to quantization. Lost details of video not appear after decompression. The better video processing algorithms and many techniques like pre-processing and low pass filters are used to reduce the compression error. The character recognition is used to find the data in written or printed document or any data source. In this character recognition, data is scanned by a special scanner. Pattern matching algorithms is used in character recognition to find character that may be in any form. In the proposed coder scanned document are compressed using video codec method. The scanned page will decomposed in to N number of blocks. Then that will arrange in sequence to build video. Video sequence is compressed using advanced video codec (H.264/AVC). The pattern matching algorithm is used to reduce the data lost during the decompression. This method will give high quality of video compression compared with conventional methods. The performance and evaluation will be shown by Peak Signal to Noise Ratio (PSNR) and Structural Similarity Metric (SSM). Simulation results are shown by using MATLAB R2013a.