复杂场景中高维曲线的Hough变换检测方法研究

项目名称： 复杂场景中高维曲线的Hough变换检测方法研究

项目编号： No.61471167

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 郭斯羽

作者单位： 湖南大学

项目金额： 64万元

中文摘要： Hough变换（HT）作为参数化曲线或模型检测方法，因其强鲁棒性和不依赖启发式信息的特点应用广泛。在复杂现实场景中，HT容易产生大量虚假结果，对高维曲线的检测性能也有待提高。本项目主要研究：1.选择适当图像特征，如梯度、纹理、视觉显著性等，对HT投票过程加权以有效抑制虚假峰值，并找到有效加权特征的快速提取方法；2.探索Hough空间分布的分析方法，获取与HT检测性能有关的空间分布特性，并据此实现HT参数的机器学习；3.基于加权和随机化等技术，寻找具有高时空性能和高检测率的一般性高维曲线HT检测方法，探索HT在高维曲线检测任务中的适用性限度；4.寻找所提HT检测方法的基于神经网络的硬件高效实现，并在两个具体问题上进行应用研究。研究成果可丰富HT相关理论，对理解人类视觉系统的相关感知过程提供有益的启发，并能克服HT的若干现有缺陷，拓宽其应用范围，提升其应用前景。

中文关键词： Hough变换；投票加权；Hough空间分布；高维曲线检测；复杂场景

英文摘要： Hough transform (HT) has been widely used as a detection approach for parametric curves and models due to its robustness and being free of heuristic information. HT usually yields large quantities of false instances when applied to real-world complex scenes. The detection performances for high dimensional curves are also to be promoted. Main research interests of this proposal are as follows. 1) The choices and rapid extraction methods of image features such as gradients, texture and visual saliency which effectively suppress the false peaks in the Hough space through weighting the votes during the HT voting process. 2) Exploration of the mothods for Hough space distribution analysis and the determination of the distribution characteristics relevant to HT detection performances, which can be used for machine learning based setting of HT algorithm parameters. 3) HT detection method based on weighting and randomization for general high dimensional curves with high time and space performances as well as high detection rates, and the exploration of the limit in the applicability of HT-based methods in high dimensional curve detection tasks. 4) Efficient hardware implementations of the proposed HT detection methods based on artificial neural networks, and case studies of applying the methods and implementations to two specific applications. The research results will enrich the relevant HT theories, and give useful clues to the understanding of the curve perception of human vision. The proposed methods can overcome some of the existing shortcomings of HT, making it applicable and promising choice for a wider range of applications.

英文关键词： Hough transform;vote weighting;Hough space distribution;high dimensional curve detection;complex scenes