为了解决冷轧薄板板形识别问题，采用基于形态学的图像处理方法。
A cold-rolled strip plate-profile recognition method was presented to improve the detection accuracy based on image morphology processing method.
板形识别与板形控制理论及数学建模则是此项技术的理论基础和关键科学问题。
As far as the technique is concerned, theoretical basis and key scientific problem is the theory and mathematic model of shape control.
板形识别与板形控制技术的智能化实现是现代板带轧机控制中的世界前沿性研究课题。
As far as the technique is concerned, the key scientific problem in the world is pattern recognition and the realization of shape intelligent control.
为了提高带材板形识别的精度，应用神经网络和最优化方法，构建了一种新的板形信号模式识别方法。
In order to improve the pattern recognition precision, using the neural network recognition and optimal method, a new pattern recognition method of shape signal was established.
为制定合理的控制策略，须对实测板形进行模式识别，并以约定的参数定量地提供给下一控制环节。
The real shape must be recognized to establish rational control strategy and the recognition results must be quantificationally provided to the next control link with promissory parameters.
本文提出了基于模糊距离的R BF网络板形缺陷模式识别法。
In this paper, we put forward using RBF network to flatness pattern recognition.
分析比较了各主要模式识别方法的特点。对板形模式识别方法的发展趋势进行了讨论。
The characteristics of various chief pattern recognition methods are analyzed and compared, and the trend of development of the method is symposiumed.
分析比较了各主要模式识别方法的特点。对板形模式识别方法的发展趋势进行了讨论。
The characteristics of various chief pattern recognition methods are analyzed and compared, and the trend of development of the method is symposiumed.
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