基于iPhone手机的数字码实时识别与应用

根据苹果手机拍摄防伪标签数字实时识别的需要,针对防伪数字字号较小的因素和苹果手机因拍摄距离的原因造成的图像缩小、数字模糊、背景复杂等问题进行处理,提高识别精度。首先通过人工选取数字码区域,并进行背景数字分离,定位获取数字图像;其次采用灰度化和二值化得到黑白图像;然后通过投影对数字码图像进行分割,并对每个数字图像进行归一化、锐化和细化;基于统计学抽取数字码的特征,采用最近邻域判别函数进行数字码识别,取得很好的识别效果。

Recognition of printed-numerical codes and its application based on iPhones

To meet the need of real time shoot and identification of numerical codes printed on goods labels, due to the small size of numerical codes and the small, fuzzy, complex images taken by iPhones from long distance, we propose a series of image processing to improve the recognition accuracy. First, we choose numerical regions manually, and then separate numerical codes from the background, thus obtaining a numerical image. Then the numerical image is transformed to a white black one by graying and binaryzation. Each numerical code image is segmented by projection method, and then they are normalized, sharpened, and thinned. We finally adopt the nearest neighbor method to recognize the numerical codes based on the extracted statistical features. Experimental results prove the high recognition accuracy.