Design And Implementation Of Text Block Segmentation System In Medical Documentation Image

In the medical and health field, the patient medical treatment process will generate a lot of paper documents. These paper documents are very important voucher in future, which can be used in many places. But these documents were handled by manually, which would bring a lot of problems: time-consuming, inefficient, not easy to retrieve statistics in the future and so on. In this case, a fast automatically data input system for medical document is needed urgently, in which, the text blocks segmentation in medical document image is an important step.To achieve text blocks segmentation in medical document image, the seal removing, skew correction, text area trimming, text blocks segmentation and other functions should be implemented. Medical Documents always contain seals, which is harmful for the text block segmentation, the removal algorithm based on R-channel threshold can effectively remove the seal; scanned images of documents always skew small angles, and the Hough Transform which was widely used to detect the skew angle for text images calculate too much, an adaptive algorithm to select image sub-region, can quickly and accurately locate the sub-region in original image for the skew angle detection, and can effectively reduce the amount of calculation; Document images always contain noise and dirt, using the boundary rectangle of the text contour combined with the size of the text algorithm, we can figure out the boundary of the text area, and accurately cut out the text area from the document.The text-block segmentation system in medical document image was designed and implemented, and the system was tested for each of the major functions and system performance. The seal removal rate reached 88.89%, skew correction correct rate reached 95.21%, the text area to trim the correct rate reached 85.78%, and the text block division correct rate reached 75.86%; the average time a single image processing is approximately 9.399 s. From the test results, the system can basically meet the needs of users.