CAJ | 학술논문

针对汉字的多样性和相似性不同于西方字母，识别相对困难的问题，提出了基于 ART 神经网络的汉字识别方法。在识别前，利用 OpenCV(开源计算机视觉库)将汉字进行图像处理，为后续识别提供输入数据；然后经 ART 神经网络对输入数据进行训练识别。采用8组相似度较高的汉字作为样本进行实验，证明了方法的有效性。
침대한자적다양성화상사성불동우서방자모，식별상대곤난적문제，제출료기우 ART 신경망락적한자식별방법。재식별전，이용 OpenCV(개원계산궤시각고)장한자진행도상처리，위후속식별제공수입수거；연후경 ART 신경망락대수입수거진행훈련식별。채용8조상사도교고적한자작위양본진행실험，증명료방법적유효성。
Ouring to the differences between Chinese and western words and the difficulty in recognition,a Chinese charac-ter recognition model based on the ART neural network is proposed. Before recognition,the Chinese characters are processed by OpenCV(open source computer vision library),which provides input data for the following recognition procedure. Then, the input data are trained and recognized by ART neural network. In the experiment,eight groups of similar Chinese charac-ters were used as samples for the sake of making the results universal. The results show that the recognition of the shape-changed Chinese characters among the provided samples is reliable and accurate.