These distortions affect the preprocessing stage. For example, projective distortions, blur, brightness changes, highlights, and so on. Secondly, with fewer restrictions for image capturing, more distortions appear. The other way is embedded recognition that leads to the necessity of fast and resource-efficient algorithms. With personal documents, sensitive banking papers, or COVID-19 test results you want to save as much privacy as possible, so the recognition on the cloud server is out of the question. In the case of mobile OCR software, two different problems arise: the constraints on computing power and uncontrolled image capturing conditions. As a possible last step, sometimes postprocessing algorithms can improve the recognition accuracy. Finally, the system performs character classification. Then, a segmentation algorithm is employed to divide the text line image into separate characters images. It tends to simplify the segmentation process. So, most of the methods start with image preprocessing, especially with image binarization. The other thing to take into account is the standard OCR workflow, as shown in the picture. Binarized scanĪs we see, the image quality can differ drastically. We captured the same document in three ways:ġ) scanned it with 300dpi with Canon CanoScan LiDE 300 and binarized the result ģ) shot a video with a web camera, split it and took a frame.Īs you can see, the modern conditions of image acquisition demand the system to be robust to very different conditions. To understand the difficulty of this problem let us begin with an example. ![]() And now it faces one of the greatest challenges - recognition of camera-captured images. The main one being the replacement of the variety of classifiers with artificial neural networks (ANNs). Since then, OCR has undergone a lot of changes. These systems processed typewritten sales reports and converted them into perfocards. ![]() In the 1950s the usage of the commercial OCR systems began. First OCR systems appeared almost simultaneously with the first digital computers.
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