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An Embedded Lens Controller for Passive Auto-Focusing Camera Device Based on SOM Neural Network

机译:基于SOM神经网络的被动式自动对焦相机设备嵌入式镜头控制器

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Recently, camera has been widely used in the mobile device in order to provide the function of photograph. In camera''s control techniques, passive auto-focusing (PAF) has become a tendency to improve the quality of image and the production cost. Basically, the sharpness measurement algorithm is used to measure the focused values of the scene captured. However, the conventional control methods are not very suit for PAF technique due to the full search is still used in PAF control, and it can not efficiently capture the image in a dynamic situation. To decrease the searching time needed, this paper presents a new controller based on SOM neural network. The proposed method is easily to be implemented as the embedded system or be designed as a slimmer and smaller mobile camera device by using a specific integrated circuit. In our study, the implementation is demonstrated by an integrated system which includes CMOS image sensor with adjustable lens, micro-controller and FPGA
机译:近来,照相机已经被广泛地用于移动设备中以提供照片的功能。在相机的控制技术中,被动自动对焦(PAF)已成为提高图像质量和生产成本的趋势。基本上,清晰度测量算法用于测量捕获的场景的聚焦值。然而,由于全搜索仍用于PAF控制中,因此传统的控制方法不太适合PAF技术,并且在动态情况下不能有效地捕获图像。为了减少所需的搜索时间,本文提出了一种基于SOM神经网络的新型控制器。通过使用特定的集成电路,所提出的方法易于被实现为嵌入式系统或被设计为更薄,更小的移动相机设备。在我们的研究中,该实现由集成系统演示,该集成系统包括带可调节镜头的CMOS图像传感器,微控制器和FPGA

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