earticle

영어

In this paper, we proposed a method to detect the rotation angle for the back side image of a container. Our technique consists of sorting the segmented characters according to the X axis, then detecting the segments belonging to the container number, after that, we divide the segments by groups having the same height, and finally the rotation angle of the image will be the average of the skewed angles related to each group. Our approach is robust, efficient and capable of handling any font and size of characters; regarding its complexity for an image having N lines and M characters, the worst CPU time usage and the worst memory usage is equal to O (NxM) while the network usage and disk usage for one image is O (1) which led –while using an old laptop- to a response time around 0.45 milliseconds to detect the rotation angle of an image when rotated from -45o to +45o with an precision error between ±0.2o. The high accuracy and the fast response time for detecting the rotation angle of container images make our approach suitable for online OCR critical applications.