This document discusses detecting the shape and characteristic sizes of irregular objects in images. Standard shapes like rectangles, circles, rhombuses and ellipses are used as templates to compare object contours to. Computer vision techniques using OpenCV analyze camera images to find the contour of each object, then calculate metrics like rectness, circless and ellipseness to determine which standard shape best matches the contour. The results of detecting shapes for different types of figures like generated, ragged, regular and irregular objects are presented.

1. Irregular objects.
Shape detection and characteristic sizes
Nizhny Tagil Technological Institute (branch)
of Ural Federal University
Sergey O. Bochkarev
Igor B. Litus
Natalia S. Kravchenko

2. Task
• Find contour of object on a
picture.
• Detect standard shape, in which
it looks like.
• Find characteristic sizes

3. Standard shapes
• Rectangle
• Circle
• Rhombus
• Ellipse

4. Standard shapes

5. Used technologies
• Camera Nikon D800 7360px × 4912px
• C#-based software
• DBMS mysql
• Computer vision library opencv

6. Used criterion: rectness
• Rectness - closeness of contour to rectangle
𝑟𝑒𝑐 =
𝑆𝑐𝑜𝑛𝑡𝑜𝑢𝑟
𝑆𝑟𝑒𝑐𝑡

7. Used criterion: circless
• Circless - closeness of contour to circle
𝑐𝑖𝑟 =
𝑆𝑐𝑜𝑛𝑡𝑜𝑢𝑟
𝑆𝑐𝑖𝑟𝑐𝑙𝑒

8. Used criterion: ellipseness
• Ellipseness - closeness of contour to ellipse
𝑒𝑙𝑙 =
𝑆𝑐𝑜𝑛𝑡𝑜𝑢𝑟
𝑆 𝑒𝑙𝑙𝑖𝑝𝑠𝑒

9. Compactness of standard shapes

10. Results of detection: generated figures

11. Results of detection: ragged figures

12. Results of detection: regular figures

13. Results of detection: irregular figures