双频感应测井仪接收机前端电路设计

【作者】 王静；

【导师】 师奕兵；

【作者基本信息】 电子科技大学 ， 测试计量技术及仪器， 2007， 硕士

【摘要】 印章作为中国社会信用体系的一种表现形式，在日常生活中发挥着非常重要的作用。随着科技的不断发展，印章制作工艺得到了很大的提高。从传统人工雕刻发展到了机械雕刻、激光雕刻等先进的制作方式。随即带来的是假冒伪劣印章在识别中的难度大大的提高，传统人工比对方法的有效性大大降低，因此出现了计算机印章自动鉴定研究。印章自动鉴定属于图像模式识别领域，其主要分为印文分割、印文配准、特征提取及特征识别几个步骤。到目前为止，已有一些很好的研究成果被应用到实际工作中。但由于印章图像的复杂性，尚有一些问题未有效解决。本文通过研究，提出了一种新的方法，成功的将脉冲耦合神经网络(PCNN)应用到印章自动识别中。利用PCNN的自动波的特性，可有效的定位印文在图像中的位置。在获得了印文所在位置后，可获得印文图像上的关键有效像素点的色彩等信息，这样就能够得到最为准确的阈值，可有效的将印文从复杂背景中分割出来。此外还提出了将主元成分分析(PCA)神经网络方法应用到印文配准的工作中。PCA方法可以通过全局分布特点，快速的将印文图像的大致方向确定，并将印文基本配准，然后再基于基本配准的印文图像，进行小范围的精确搜索，达到最佳的精确配准效果。该方法同样得到了较好的结果。为了验证PCNN及PCA方法在实际应用中的效果，本文通过将这些方法结合实际印章图像用MATLAB进行了仿真试验。通过试验表明，本文提出的结合PCNN的方法可准确的将有效印文从复杂背景中分割出来。同时，通过与PCA结合的方法可非常精确的将印文图像进行配准，对后续的特征提取及识别工作提供了很好的支持。进一步，为了将研究成果紧密的结合到真实的应用环境中，本文设计并实现了智能印章识别系统(IntelliSIS)，本文对IntelliSIS系统的设计框架、系统实现、系统性能等作了详细介绍。更多还原

【Abstract】 As the form of credit system of Chinese society, seal is very important for this. By the development of technology, the producing techniques have a great improvement. With this improvement, the difficulty of fake seal recognition is also being higher and higher and the validity of traditional manual comparison is greatly low. Thus the automatic computer identification research arose. Automatic seal identification belongs to pattern recognition domain and includes seal segmentation, seal registration, feature extraction and feature identification these steps. Recently, some good research results have been applied in practice. But because of the complexity of seal images, there are still many problems need to be resolved.According to research, we have proposed a new method, applying the Pulse Couple Neural Network (PCNN) in automatic seal identification. By using the auto wave character of PCNN, this method can locate the seal in the image. After we get the location of the seal imprint we can obtain the available critical color information of the seal imprint itself and segment seal texture from the image efficiently by using the accurate threshold. At the same time we also applied the Principal Components Analysis (PCA) neural network in seal registration successfully. The PCA can obtain the approximate direction of the seal imprint by using the global distribution of the image pixels of seal imprint. After this it can use the local search method for precisely registration and get a very good result.To validate the PCNN and PCA methods in practice, we did the simulation by using the real seal images and PCNN and PCA in MATLAB. Through the experiment, the PCNN method is efficient, it can segment seal texture from the whole seal image precisely and PCA method can also register the seals precisely. This will helpful to the subsequent steps. Furthermore, to integrate the methods in a practical applied environment, we have designed and implemented an Intelligent Seal Identification System (IntelliSIS), it will introduce the details of system framework, implementation and system performance in this article.更多还原