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From the project of the date and time reading in the Radar images, the OCR templates technique was applied because some Radar images do not have date and time information in their properties. The method had the problems that the Radar images could not be retrieved when the month names are changed and then the new month name templates had to be created. Therefore, this work has applied Tesseract OCR library to help read the date and time images and used Fast Normalized Cross-Correlation theory to enhance the performance of the template matching and to retrieve more Radar images. The accuracy of results in this program using Fast Normalized Cross-Correlation with OCR templates was 86 percent.

The Global Satellite Mapping of Precipitation or GSMaP data which is used to display the rainfall data was used to analyze and create the rainfall forecasting model. This work is the evaluation of this rainfall forecasting model which is the short-term forecast. The GSMaP forecasting data were matched with the GSMaP history data and calculate their similarity values by applying the original image matching method. The modification of Rainfall Forecasting Model and its evaluation that applied the original image instead of the image hash improve the accuracy of rainfall forecasted results.