1985 Fiscal Year Final Research Report Summary
Fast Range-lmage Generator by using Gray coded pattern projection
| Project/Area Number |
59850070
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| Research Category |
Grant-in-Aid for Developmental Scientific Research
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
1984 – 1985
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| Keywords | Range picture / Three dimensional measurement / Robot vision / lmage understanding / 三次元構造認識 |
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| Research Abstract |
This project deals with methods to get range picture and applications and utilizations of range picture for Three-dimensional(3D) object recognition. We have developed new type of range-imaging systems using pattern projection. Pattern projector and CCD(Charge Coupled Device) video camera realize the range measurement system utilizing space encoding based on triangulation method. Both the experimental system using Gray coded pattern ligh, and one using binary image accumulation with half-plane light, are produced. We have experimental results. The former approach gets accurate range picture stably and quickly with a few (n) of light projection, instead of scanning a slit light at 2n positions in turn. The latter approach realizes range finder constructed with very simple equipments. It is confirmed that these systems may be suited for the industrial use, for example, shape inspection, shape measurement and also robot vision.
Gray coded pattern projection method requires the switching of light-masks. Experimental pattern projector produced for the system have mechanical light-mask structure. Non-mechanical pattern projector, such as LCD(Liquid Crystal Device) shutter, are wished for industrial use. Dot matrix LCD display is experimented elementally. It is confirmed that the contrast of projection is considerable good and the influence of gap of electrode can be ignored.
Range picture are very convenient for scene analysis including segmentation, description, and understanding of 3D objects. In order to recognize the shape of 3D objects, the following methodologies have been studied. Quadric surface approximation is applied to classify the spape of surface into some categories, for instance, ellipsoid, paraboloid and cone. Ring operator and curvature operator can detect feature points in range picture.
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