摘要
SSDA算法(序贯相似性检测)是针对一般模板匹配算法计算量大而提出的减少计算量的误差累计算法.但它同样需要依据图像之间的像素点对进行计算,从而对字符图像的变形敏感.在从事车牌自动识别课题研究中应用SSDA算法进行字符识别过程中,为了减小字符图像变形,在字符倾斜校正、字符二值化、字符切分和字符归一化过程中都围绕其加以改进或提出新算法.
The sequential similarity detection algorithm （SSDA） is applied to image matching because the calculating work is considerable by using the algorithm of common template matching. But the SSDA still needs to compute the sum of errors of the corresponding pixels between two images,so the SSDA is sensitive to distortion of characters. In this paper,the SSDA algorithm is improved in order to reduce the distortion in the following fields：character skewness correction,character binarization and character normalization.
出处
《应用科技》
CAS
2006年第9期37-40,47,共5页
Applied Science and Technology
关键词
SSDA模板匹配
字符倾斜校正
字符二值化
字符归一化
字符切分
SSDA
character skewness correction and segmentation
character binarization
character normalization
character segmentation
