图像处理中模糊算法问题的分析

图像处理是计算机常用技术之一,模糊算法的运用有助于提高图像处理的效果。传统图像处理存在诸多弊端,影响了用户获取信息的便捷性。本文分析了图像处理的基本操作内容,并阐述了模糊算法在图像处理流程中的运用,以进一步提升原始图像处理的效果。     

一个与Ethernet兼容的多媒体实时传输协议的设计

为适应办公自动化的需要, 探讨了一种集图像( 声音)/ 数据服务于一体的多媒体传输协议, 对协议的集成策略及执行过程进行了详尽说明, 并给出了协议进程的形式描述。经仿真运行证明, 用该协议实现的介质访问控制器( MAC) 能与传统的Ethernet MAC 共存于一个Ethernet 网上。该协议能满足图像( 声音) 的实时传输要求, 该协议只是对MAC 而言的, 因而对现存的数据链路层以上的协议无影响。     

非线性滤波在射线图像降噪增强中的应用

射线数字成像是当前射线检测与诊断技术发展的方向，图像降噪增强是提高射线成像检测灵敏度和分辨力的关键。重点探讨以排序滤波为代表的非线性滤波图像降噪增强方法，对射线图像的处理表明，线性滤波在降噪的同时会引起较大的边级模糊，而排序滤波不仅降低噪声且能保持图像细节，提高图像质量效果明显。     

Application of neuro-fuzzy techniques in oil pipeline ultrasonic nondestructive testing

This paper presents a novel approach to the problem of nondestructive pipeline testing using ultrasonic imaging. The identification of the flaw type and its dimensions are the most important problems in the pipeline inspection. Unlike typical methods, a decision based neural network is used for the detection of flaws. We train a generalized regression neural network to determine the dimensions of the corrosions and generate the whole image of both the internal and external walls of the oil pipeline. As an improvement to the detection algorithm, we introduce fuzzy decision-based neural network algorithms for the detection and classification of the corrosions. The simulation and experimental systems results show that these new methods outperform the existing methods.     

Sensing, modeling and control for laser-based additive manufacturing

Laser-Based Additive Manufacturing (LBAM) is a promising manufacturing technology that can be widely applied to part preparation, surface modification, and Solid Freeform Fabrication (SFF). A large number of parameters govern the LBAM process. These parameters are sensitive to the environmental variations, and they also influence each other. This paper introduces the research work in RCAM on improving the performance of the LBAM process. Metal powder delivery real-time sensing and control is studied to achieve a controllable powder delivery for fabrication of functionally graded material. A closed-loop control system based on infrared image sensing is built for control of the heat input and size of the molten pool in the LBAM process. The closed-loop control results show a great improvement in the geometrical accuracy of the built features. A three-dimensional finite element model is also established to explore the thermal behavior of the molten pool in the closed-loop controlled LBAM process.     

Characterisation of mortar morphology in thin sections by digital image processing

A digital imaging approach was applied to investigate mortar morphology in thin sections; in particular, the binder/aggregate ratio and the grading curve of five mortar bars were attained by digital image processing (DIP), using the Image Pro Plus 4.1 software package. The imaging procedure employed image segmentation, to extract mortar aggregate, and image filtering, to fix grain boundaries. The results show that digital image processing may be considered as an alternative method to mechanical sieving for the characterisation of mortar morphology, as it appears to be quicker and more accurate than the traditional method. However, digital image processing exhibits limits, which are discussed in the text.     

The influence of grinding technique on the liberation of clinker minerals and cement properties

This paper describes a study of the relationship between the physical, chemical and mineralogical parameters of cement products obtained by different grinding mechanisms namely high pressure grinding rolls (HPGR) and ball milling, and their effects upon the properties of cements prepared from the ground clinker. Samples were prepared as narrow size fractions and also as distribution samples. Characterization parameters were ascertained by using XRF, laser sizing, Blaine and BET surface area and image analysis methods. HPGR grinding resulted in higher degrees of liberation of clinker phases arising from the intergranular breakage along the grain boundaries compared to ball mill grinding. As for service properties, water demand of HPGR products was higher than ball mill products resulting from high micro fissured structure. Despite high liberation of particularly alite mineral in HPGR grinding, the compressive strength of ball mill products was slightly higher than HPGR products for narrow size samples. Finally, particle size distribution effect on strength was more obvious for distribution samples; generally ball milling gave higher strength values.     

Ensemble of multiple instance classifiers for image re-ranking

Text-based image retrieval may perform poorly due to the irrelevant and/or incomplete text surrounding the images in the web pages. In such situations, visual content of the images can be leveraged to improve the image ranking performance. In this paper, we look into this problem of image re-ranking and propose a system that automatically constructs multiple candidate “multi-instance bags (MI-bags)”, which are likely to contain relevant images. These automatically constructed bags are then utilized by ensembles of Multiple Instance Learning (MIL) classifiers and the images are re-ranked according to the final classification responses. Our method is unsupervised in the sense that, the only input to the system is the text query itself, without any user feedback or annotation. The experimental results demonstrate that constructing multiple instance bags based on the retrieval order and utilizing ensembles of MIL classifiers greatly enhance the retrieval performance, achieving on par or better results compared to the state-of-the-art.