CAJ | 학술논문

纸币面额识别是纸币清分过程中的一个很重要的步骤，目前对纸币面额识别的研究主要集中于灰度图像上，还没有人使用彩色图像做过纸币面额识别的研究。在此提出一种基于HSV空间的纸币面额识别算法，根据待识别纸币和不同面额纸币的H、S、V分量均值的色差大小来对纸币的面额进行识别。在此首先使用扫描仪扫描到的高分辨率的图像进行实验，证明了算法的正确性。然后采用智能点验钞机采集到的低分辨率的图像进行实验，针对低分辨率图像，提出采用直方图均衡化的改进算法，分类准确率达到98.78%，证明本算法能够满足实际应用的需要。
지폐면액식별시지폐청분과정중적일개흔중요적보취，목전대지폐면액식별적연구주요집중우회도도상상，환몰유인사용채색도상주과지폐면액식별적연구。재차제출일충기우HSV공간적지폐면액식별산법，근거대식별지폐화불동면액지폐적H、S、V분량균치적색차대소래대지폐적면액진행식별。재차수선사용소묘의소묘도적고분변솔적도상진행실험，증명료산법적정학성。연후채용지능점험초궤채집도적저분변솔적도상진행실험，침대저분변솔도상，제출채용직방도균형화적개진산법，분류준학솔체도98.78%，증명본산법능구만족실제응용적수요。
Denomination recognition of banknote is a very important step in the process of paper currency sorting. The cur?rent research of the denomination recognition of banknote is mainly concentrated in the gray image,but no one uses color image for the research. A banknote denomination recognition algorithm based on HSV space is presented in this paper, which recognizes the denomination of banknote according to the color scale of H,S,V component of different banknotes. The correctness of the algorithm was proved by the high resolution images got by a scanner. The low resolution images collected by the smart currency detector were employed to carry out an experiment for recognition of low resolution images. An improved algorithm of using histo?gram equalization is proposed,whose classification accuracy rate reaches 98.78%. It proves that this algorithm can meet the needs of practical application.