Guest Editorial: Special issue on computer vision and machine learning for healthcare applications

Pattern Analysis and Applications -     

Algorithmic techniques for computer vision on a fine-grainedparallel machine

The authors describe several fundamentally useful primitive operations and routines and illustrate their usefulness in a wide range of familiar version processes. These operations are described in terms of a vector machine model of parallel computation. They use a parallel vector model because vector models can be mapped onto a wide range of architectures. They also describe implementing these primitives on a particular fine-grained machine, the connection machine. It is found that these primitives are applicable in a variety of vision tasks. Grid permutations are useful in many early vision algorithms, such as Gaussian convolution, edge detection, motion, and stereo computation. Scan primitives facilitate simple, efficient solutions of many problems in middle- and high-level vision. Pointer jumping, using permutation operations, permits construction of extended image structures in logarithmic time. Methods such as outer products, which rely on a variety of primitives, play an important role of many high-level algorithms     

CAD off-line programming for industrial machine vision

CAD/CAM tools are essential components of the computer-integrated factory. Up to now, they have been used for tasks such as the simulation and path programming of numerically controlled machine tools, and sometimes industrial robots. The CAD-vision interconnection described here enables us to program parts learning on the workstation, to download piece features in the vision system for inspection on the production line, to simulate the recognition process on a set of parts stored in the computer, and to update vision files after modifications in the CAD system database.     

基于LabVIEW的网络机器视觉检测系统

针对生产过程中需要实时监测零件尺寸的情况,采用一种网络机器视觉尺寸测量系统,该系统以LabVIEW为平台,配以1394摄像头和图像采集卡,利用一定的图像处理技术完成视觉检测,利用DataSocket技术实现图像的网络实时发布和客户端图像的接收。经过测试,从图像采集、处理和发布系统耗时不超过280m s,该系统开发周期短,检测速度快,充分发挥了虚拟仪器技术的功能强大、扩展性强的特点。     

A knowledge-based vision system for industrial applications

This paper introduces a knowledge-based vision system for industrial environments. It is designed to control a cell in an assembly system. The images from the environment are taken as gray scale images. Based on a single image, the system has to recognize type and position of the recorded parts and to control their placement in the environment for further manipulation. This requires the explicit representation of rich task-specific knowledge. The effort to adapt our system to new tasks is very small. Thus, it is very important that the system is able to support major parts of the activities that are necessary for the acquisition of new knowledge. The system consists of three components-image segmentation, knowledge acquisition, and matching-which are described in detail. All the methods presented were tested using different parts of an electric motor as an example.     

Special issue on omnidirectional vision and its applications

Machine Vision and Applications -     

基于机器视觉的工矿现场粉尘实时监测

针对传统粉尘监测方法实时性差、覆盖面不全的问题,提出了2种基于机器视觉的工矿现场粉尘实时监测系统设计方案,即基于单目视觉的粉尘监测系统和基于双目视觉的粉尘监测系统。基于单目视觉的粉尘监测系统采用帧差法、腐蚀膨胀算法等实现对视场内粉尘目标的快速识别;基于双目视觉的粉尘监测系统在单目视觉粉尘监测系统的基础上,利用标定靶,通过空间三维重建实现粉尘定位。实验结果表明,基于单目视觉的粉尘监测系统可以捕捉粉尘团生成的过程,实时处理速率为4帧/s;而基于双目视觉的粉尘监测系统可以进一步测量粉尘团位置信息,定位误差在10%以内。     

A dynamic associative processor for machine vision applications

The use of massively parallel associative processors as coprocessors for accelerating machine vision applications is considered. They achieve very fine granularity, as every word of memory functions as a simple processing element. A dense, dynamic, content-addressable memory cell supports fully parallel operation, and pitch-matched word logic improves arithmetic performance with minimal area cost. An asynchronous reconfigurable mesh network handles interprocessor communication and image input/output, and an area-efficient pass-transistor circuit counts and prioritizes responders. Some applications are discussed     

Design and application of industrial machine vision systems

In this paper, the role and importance of the machine vision systems in the industrial applications are described. First understanding of the vision in terms of a universal concept is explained. System design methodology is discussed and a generic machine vision model is reported. Such a machine includes systems and sub-systems, which of course depend on the type of applications and required tasks. In general, expected functions from a vision machine are the exploitation and imposition of the environmental constraint of a scene, the capturing of the images, analysis of those captured images, recognition of certain objects and features within each image, and the initiation of subsequent actions in order to accept or reject the corresponding objects. After a vision system performs all these stages, the task in hand is almost completed. Here, the sequence and proper functioning of each system and sub-systems in terms of high-quality images is explained. In operation, there is a scene with some constraint, first step for the machine is the image acquisition, pre-processing of image, segmentation, feature extraction, classification, inspection, and finally actuation, which is an interaction with the scene under study. At the end of this report, industrial image vision applications are explained in detail. Such applications include the area of automated visual inspection (AVI), process control, parts identification, and important role in the robotic guidance and control. Vision developments in manufacturing that can result in improvements in the reliability, in the product quality, and enabling technology for a new production process are presented. The key points in design and applications of a machine vision system are also presented. Such considerations can be generally classified into the six different categories such as the scene constraints, image acquisition, image pre-processing, image processing, machine vision justification, and finally the systematic considerations. Each aspect of such processes is described here and the proper condition for an optimal design is reported.     

Guest editorial: special issue on modeling and mitigation techniques for software aging

Software Quality Journal -     

A real-time mathematical computer method for potato inspection using machine vision

Detection of external defects on potatoes is the most important technology in the realization of automatic potato sorting stations. This paper presents a hierarchical grading method applied to the potatoes. In this work a potato defect detection combining with size sorting system using the machine vision will be proposed. This work also will focus on the mathematics methods used in automation with a particular emphasis on the issues associated with designing, implementing and using classification algorithms to solve equations. In the first step, a simple size sorting based on mathematical binarization is described, and the second step is to segment the defects; to do this, color based classifiers are used. All the detection standards for this work are referenced from the United States Agriculture Department, and Canadian Food Industries. Results show that we have a high accuracy in both size sorting and classification. Experimental results show that support vector machines have very high accuracy and speed between classifiers for defect detection.     

Special issue on machine learning for security and privacy: advancing the state-of-the-art applications

Neural Computing and Applications -