Abstract
3-D Vision is now a common sensing method frequently used in industrial applications. With the convenience of an uncalibrated system, 3-D reconstruction by a self-calibration technique is possible, but always incomplete or unreliable. This paper presents a novel method to analyze the blur distribution in an image and find the optimal focusing distance so that additional constraints can be used to generate absolute measurement of the models. With the assumption of a Gaussian distribution model of the point spread function, this paper applies two theorems to efficiently compute the defocusing extent on stripe edges. Because the blurring diameter implies the distance from the sensor to the surface, we can upgrade the 3-D map obtained from self-calibration with the known scaling factor. Through theoretical and experimental analysis, we find that not only the technology is feasible, but also both the accuracy and the efficiency are satisfactory.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
