细胞神经网络图像处理的大规模并行方法

Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94) Pub Date : 1994-12-18 DOI:10.1109/CNNA.1994.381638

Giovanni Adorni, V. D'Andrea, G. Destri

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引用次数: 5

摘要

低级图像处理是一个关键阶段，因为后续“更智能”步骤的结果取决于第一处理阶段的输出质量。在这项工作中，我们提出了一种边缘检测滤波算法，严格面向增强某些物体的边缘，在典型的真实图像噪声环境中，使用一些“先验的”已知特征。我们还描述了该算法在道路图像分析中的应用，其目标是增强交通标志

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A massively parallel approach to cellular neural networks image processing

Low-level image processing is a critical phase, since the results of following "more intelligent" steps depend on the output quality of the first processing stages. In this work we present an edge detection filtering algorithm, strictly oriented to enhance the edge of some objects, in a typical real image noisy context, using some "a priori" known characteristics. We describe also an application of this algorithm to the analysis of road images, where the goal is the enhancement of traffic signs.<>

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Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94)

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