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Machine Vision Applications Case Study No. 2 Matt, grey, laminate objects: shape analysis & robotic handling.

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Presentation on theme: "Machine Vision Applications Case Study No. 2 Matt, grey, laminate objects: shape analysis & robotic handling."— Presentation transcript:

1 Machine Vision Applications Case Study No. 2 Matt, grey, laminate objects: shape analysis & robotic handling

2 Laminate Objects on a Flat Table

3 Lighting and Viewing Back-lighting (Methods ) Histogram of back-lit object –Bimodal –Effects of non-uniform background Effect of shiny surface –Object appears smaller –Cure: Method 19 Other methods –Retro-reflective back-ground (Method 93) –UV lighting & Fluorescent back-ground (Method 94) –Projecting multiple shadows (Method 95)

4 Preprocessing Fixed-level thresholding - not secure Histogram analysis & thresholding - better Edge detection and thresholding –Problem of noise Blob isolation

5 Position Centroid –2D array –Run code –Chain code Minimum area rectangle Circumcircle

6 Orientation Principal axis (min 2 nd order moments) Centroid to centroid of concavity (lake/bay) Centroid to most distant edge point Concavity to concavity Centroid to corner Corner to corner Radon / Hough transform

7 Shape Recognition Shape factor: area/perimeter 2 Convex hull Minimum area rectangle Circumcircle Moments Analysis of edge function –R(  ) –R(d) –Fourier analysis Concavity tree Skeleton

8 Additional methods of analysis Concavity tree Skeleton –Limb ends –Joints Edge parsing Convex decomposition

9 Binary Image Analysis: advanced applications 3D inspection –Range maps –Manufactured goods –Natural and food products Assembly (jig-saw problem) 2D packing 3D packing Partially occluded shapes –Bin picking problem Optical character recognition (OCR) Military target recognition (VIS, IR or radar)


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