Textural Measure for Medical Words Characterization Applied to Script Identification in Bilingual Context

The objective of this work is to contribute to the analysis and understanding of medical documents taken from health institutions in Saudi Arabia. The project aimed to use intelligent technologies and image processing tools to the automation of processing the medical documents. This consists particularly to assist medical staff to the treatment of the different medical forms in order to facilitate the storage of the important information and their centralization. As we worked on bilingual context, we proposed a system for identifying Arabic and Latin texts whether taped or manuscripted. In this way, we can identify the extracted blocks from different regions of interest and distribute them to different OCR systems to recognize them. We used SGLD as a texture measure of the image writing shapes. Then, we calculated Haralick descriptors that characterize them. The resulting recognition ratios were very efficient and promising.