Using morphology in document image processing
Vicente P. Concepcion, Matthew P. Grzech, Donald P. D'Amato · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
To improve the readability, image compression, and optical character recognition (OCR) system performance for two-tone (binary) text image data, we investigated morphological methods of image processing. We found them to be fast and effective not only with noise text images but with relatively noise-free images as well. Using morphology, we improved text image readability as judged in a blind test, increased compression ratio using CCITT Group 4, and reduced OCR error (cluster) rates in a commercial omnifront scanner.