Abstract As a core component of the Marine engine, crankshaft crank is required to have high surface quality ensure that ship does not fail during voyage. After analysing defect characteristics, aiming at problems such as inaccurate detection single feature in bend defect, which leads poor effect, classification method based on machine vision was proposed. The recognition accuracy can reach 97....

Vision is an ideal sensor modality for intelligent robots. It provides rich information on the environment as required for recognizing objects and understanding situations in real time. Moreover, vision-guided robots may be largely calibration-free, which is a great practical advantage. Three vision-guided robots and their design concepts are introduced: an autonomous indoor vehicle, a calibrat...

The research on machine vision focuses on problems in texture analysis, color and face image analysis, document image analysis, tracking and motion estimation, 3D modeling and camera calibration, and visualization-based user interfacing. The research on intelligent systems concentrates on context-aware mobile systems, intelligent service robots, neural network methodology for signal analysis, a...

When teleoperating a robot using video from a remote camera, it is difficult for the operator to gauge depth and orientation from a single view. In addition, there are situations where a camera mounted for viewing by the teleoperator during a teleoperation task may not be able to see the tool tip, or the viewing angle may not be intuitive (requiring extensive training to reduce the risk of inco...

In this editorial we brie ̄ y discuss interaction between two important areas of arti® cial intelligence: computer vision (CV ) and machine learning (ML ). Although the two ® elds have a long-standing tradition and can be considered technologically mature, past research in applying ML techniques to CV problems has been limited. After a short introduction in the ® elds of computer vision and mach...

Shatadal, P., Jayas, D.S., Hehn, J.L. and Bulley, N.R. 1995. Seed classification using machine vision. Can. Agric. Eng. 37:163-167. This paper reports the results of applying digital image analysis in conjunction with statistical pattern recognition to measure the size and shape features of various seed types and to classify them into the primary grain, small seed, and large seed categories. Th...

This paper shows how to reduce the computational cost for a variety of common machine vision tasks by operating directly in the compressed domain, particularly in the context of hardware acceleration. Pyramid Vector Quantization (PVQ) is the compression technique of choice and its properties are exploited to simplify Support Vector Machines (SVM), Convolutional Neural Networks(CNNs), Histogram ...