摘要
本文以焦化厂炉号自动识别为研究背景,基于MATLAB软件并运用图像处理的方法对从工业现场采集到的数字字符图像进行处理,然后采用神经网络的方法对图像中的字符进行识别仿真,从而达到对工业现场中的字符识别要求。该方法与传统的方法相比较,具有较高的识别效率,且通用性较强。
This paper＇s research background is the auto-recognition of cook oven number in the cokeoven plant. It is based on the software MATLAB, and uses the image processing methods to deal with the pictures which are sampled in the industry field, and then the neural network algorithm is applied to stimulant the recognition of the numerical characters in the picture, so that it can fit for producing need. Compared with the traditional methods, this algorithm has good recognition efficiency and versatility.
出处
《微计算机信息》
北大核心
2007年第04X期299-301,共3页
Control & Automation
基金
国家科技攻关计划项目(2005BA102C)
