A METHOD OF AUTOMATIC SKEW NORMALIZATION FOR INPUT IMAGES

It becomes essential in practice to improve a processing rate and to d ivide an image into small segments adjusting a limited memory, because image filing systems handle large images up to Al size. This paper pr oposes a new method of an automatic skew normalization, comprising a h igh-speed skew detection and a distortion-free dividing rotation. We h ave evaluated the proposed method from the viewpoints of the processin g rate and the accuracy for typed documents. As results, the processin g rate is 2.9 times faster than that of a conventional method. A pract ical processing rate for Al size documents can be achieved under the c ondition that the accuracy of a normalized angle is controlled within 0.3 degrees. Especially, the rotation with dividing can have no error angle, even when the Al size documents is divided into 200 segments, w hereas the conventional method cause the error angle of 1.68 degrees.