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The stereo vision method has the potential to detect the dimensions of hot forgings.
A machine vision method for measuring normal strain with high precision is presented.
The percentage errors in the workpiece diameter determined by the vision method compared to the manual measurement using a digital calliper were established for three different turning speeds.
To overcome these problems we have developed a multi-baseline stereo vision method which uses more than two images obtained from multiple non-co-linear viewpoints.
However, it is necessary for the stereo vision method to obtain clear image, and to extract and match rapidly feature points of hot forgings.
By processing images extracted from Google Street View API– using a computer vision method based on joint Histograms of Oriented Gradients and Color– traffic signs were detected and classified into four categories of regulatory, warning, stop, and yield signs.
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Later sections deal with injuries, ocular conditions associated with systemic disease, disorders of vision, methods of examining the eye, and devices for correcting visual defects.
We also compare the proposed system to other stereo vision methods reported.
In such applications, a sequence of computer vision methods is applied.
Modern surveillance systems can monitor people, cars or objects by using computer vision methods.
There is currently a strong trend towards the deployment of advanced computer vision methods on embedded systems.
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