基于DSP的机动车抗眩目系统设计

为了解决车辆在夜间行驶时,对面车灯给驾驶员造成的眩目问题,提出了一种机动车抗眩目系统的设计方案.采用视频解码芯片SAA7111A和视频编码芯片AL250完成视频信号的A/D和D/A转换;利用数字信号处理器DSP对亮度值过高的像素点进行消亮处理,以达到抗眩目的目的;可编程逻辑器件CPLD完成对整个系统的逻辑控制以及提供存储器写数据的地址.系统经实际运行,性能稳定,抗眩目效果明显.     

图像检索中的主动学习及其可测量性

主动学习对于复杂、主观、使用少量训练实例的图像检索查询具有非常有效的作用。在图像检索中应用主动学习与支持向量机相结合的方法进行相关反馈,通过两者的互补来有效地提高图像检索的精度。对比了推理算法、简单主动算法以及角度多样性算法3种主动学习算法,并研究了最好的样本选择策略。还讨论了主动学习中概念复杂度的可测量性,并对未来的研究方向提出了建议。相信随着这些可测量性问题被重点提出,主动学习的成果可以被广泛应用。     

MATLAB图像处理在水产养殖中的应用

介绍了一种通过MATLAB图像处理的方法,对水产养殖中鱼的病变情况进行监控的系统。根据中值滤波的原理,对灰度图像进行滤波,抑制噪声;根据二值化原理,将灰度图像进行二值化处理;根据收缩与扩张的原理,编写程序,对二值图像进行数次收缩与扩张,以达到去除杂质点的目的。最后采用区域矩特征的概念,找出判断鱼类出现病变的判断依据,即零阶矩,也就是白色像素的面积,只要统计出白色像素的数目,与统计数据相比较,即可判断出是否出现鱼类病变等异常情况。     

一种实用的夜间航空图像增强算法

夜间航空图像的增强处理是图像处理的一项重要内容。本文提出了一种能用硬件实现的夜间航空图像增强算法，视觉效果改善明显，更适合于人眼观察和判读，是一个实用性很强的算法。     

在VC中利用Kodak控件采集图像

本文在详细介绍Kodak图像扫描控件的属性和方法上,在VC＋＋中用Kodak图像扫描控件实现上位机的动态采集外部图像数据.     

图像编码中的容错方法分析

随着信息社会的到来,互联网以及正在迅速发展的移动通信技术,逐渐成为人们获取信息的中心。而这些信息的传输都必须由具有较强鲁棒性的压缩数据来保证。所以,在有干扰的信道中如何保护传输的压缩数据不受干扰成为人们关注的问题。针对现代信息中的最主要的图像数据的传输问题,对一些差错控制方法,特别是在JPEG2000及MPEG-4标准中所采用的新的容错工具和方法进行了较详细地分析。     

衍射图像的信号采集和数据处理

针对衍射图像边缘弥散状态不易切准的问题，运用光电积分的方法确定采集点，然后将二值化的数据通过计算机采用最小二乘法进行计算，从而保证了测量结果的正确性     

Colour classification by neural networks in graphic arts

This paper presents a hierarchical modular neural network for colour classification in graphic arts, capable of distinguishing among very similar colour classes. The network performs analysis in a rough to fine fashion, and is able to achieve a high average classification speed and a low classification error. In the rough stage of the analysis, clusters of highly overlapping colour classes are detected. Discrimination between such colour classes is performed in the next stage by using additional colour information from the surroundings of the pixel being classified. Committees of networks make decisions in the next stage. Outputs of members of the committees are adaptively fused through the BADD defuzzification strategy or the discrete Choquet fuzzy integral. The structure of the network is automatically established during the training process. Experimental investigations show the capability of the network to distinguish among very similar colour classes that can occur in multicoloured printed pictures. The classification accuracy obtained is sufficient for the network to be used for inspecting the quality of multicoloured prints.     

Polarization Phase-Based Method For Material Classification In Computer Vision

A robust and accurate polarization phase-based technique for material classification is presented. The novelty of this technique is three-fold in (i) its theoretical development, (ii) application, and, (iii) experimental implementation. The concept of phase of polarization of a light wave is introduced to computer vision for discrimination between materials according to their intrinsic electrical conductivity, such as distinguishing conducting metals, and poorly conducting dielectrics. Previous work has used intensity, color and polarization component ratios. This new method is based on the physical principle that metals retard orthogonal components of light upon reflection while dielectrics do not. This method has significant complementary advantages with respect to existing techniques, is computationally efficient, and can be easily implemented with existing imaging technology. Experiments for real circuit board inspection, nonconductive and conductive glass, and, outdoor object recognition have been performed to demonstrate its accuracy and potential capabilities.     

一种融合PCA 和KFDA 的人脸识别方法

提出一种融合PCA和KFDA的人脸识别方法，即在进行非线性映射之前，首先利用经典的主分量分析(C—PCA)进行降维，然后执行KFDA．为进一步降低整个算法的计算时问，又提出一种I—PCA KFDA方法，它直接基于图像矩阵的主分量分析(I—PCA)．ORL标准人脸库的试验结果表明，与现有的核Fisher鉴别分析方法相比，两种方法可将特征抽取的速度分别提高3倍和7倍，其识别精度没有丝毫的降低．