Study Of Pre-Processing And Segmentation Algorithm For Character Images With Complex Backgroung

In the industrial field, the application of digital image processing in pattern recognition plays a very important role for production management and quality tracking of products. Traditional image processing algorithms provide basis methods for us to solve problems, but the actual image is often been interfered with much noise and has image degradation. Using normal methods to process image can not adapt to the needs of people, so it is necessary to have a further study on image processing algorithm.The object of this paper is coded character image of work-piece with complex background, the paper studies the digital image pre-processing and segmentation algorithm for character recognition, and focuses on normal methods of image enhancement, image de-noising and image segmentation. Based on the relevant theories, the design and implementation of pre-processing and segmentation algorithm for character recognition are showed in this paper, tilt correction and character positioning algorithms of divided characters are also conducted.The actual test results show that, in the situation of smaller impact on the target object, the image processing algorithm designed in this paper has a good suppression and removal effect on a large amount of noise in the image, and characters can get correct segmentation. In addition, using the tilt correction algorithm mentioned in this paper makes split characters well corrected, and character positioning is also accurate in the template images. The average runtime of the overall algorithm process implemented in this paper is about700ms, of which character pre-processing and segmentation part is about100ms.