Abstract: To detect cataplasm's uniformity, a method based on fuzzy pattern recognition was proposed. According to the spatial and temporal correlation of pixels and the fuzziness of character boundary, the fuzzy theory was introduced and the fuzzy algorithm was used to recognize and classify the pixels' value. The CycloneⅡ Field-Programmable Gate Array (FPGA) of Altera was chosen, and the modeling and realization were performed by making use of Verilog HDL. The detection system passed the simulation and verification. In the on-line detection system, after analyzing, processing and recognizing the data of digital video, cataplasm's uniformity detection was completed. According to the statistic results, the accuracy of fuzzy pattern recognition in digital image signals is up to 95%. After experiments and online detection, the feasibility of fuzzy pattern recognition and the reliability of this quality detection system are verified.

Key words: fuzzy set theory, pattern recognition, cataplasm, uniformity detection, technology of Field-Programmable Gate Array (FPGA)

摘要： 为实现对巴布剂涂布过程中均匀度的检测，提出一种基于模糊模式识别的检测方法。根据采集图像像素点之间的空间和时间相关性及其特征界限的模糊性，引入模糊集理论，运用模糊算法对像素点的灰度值进行识别分类。检测系统采用基于CycloneⅡ系列的FPGA技术，运用Verilog HDL硬件语言对系统完成建模与实现，并且通过了仿真和验证。通过在线测试，对视频数据流进行分析、处理和识别，实现对涂布过程中巴布剂均匀度的检测，根据统计结果，正确率达到95%。检测结果证明了模糊模式识别算法的可行性和检测系统的可靠性。

关键词: 模糊集理论, 模式识别, 巴布剂, 均匀度检测, FPGA技术