Improvement And Implementation Of QR CODEDecoder Recognition Rate

• Main Authors: Teng,Kai-Chung, 鄧凱鐘
• Other Authors: Sheu,Jia-Shing
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/82546624763737615407

碩士 === 國立臺北教育大學 === 資訊科學系碩士班 === 100 === QR CODE image can be captured by digital video camera. There are many factors to cause QR CODE decoding failure, low quality image is one of reason. Focus is an important factor to affect quality of image. This thesis will discuss the factor of out of focus with QR CODE image and then to improve the recognition of the contents existing in the QR CODE image. Many researches had used the Pillbox Filter (Circular averaging filter) method to simulate the out of focus image, the Pillbox Filter is also adopt in this investigation for improving the recognition of a captured QR CODE image. In this thesis, a blurred QR CODE image is separated to 9 levels. In the experiment, using four different quantitative approaches to reconstruct and decode an out of focus QR CODE image. Four methods were used to compare the nine blurred QR CODE reconstruction image, the final experimental results show that the ability to improve the identification