Howtosignalprocessing
- What is convergence in image processing?
- What are the approaches used in thinning?
- What is thinning in computer vision?
- What do you mean by thickening and thinning?
What is convergence in image processing?
Convergence is the ability to turn the two eyes inward toward each other to look at a close object. We depend on this visual skill for near-work activities such as desk work at school, working on a smartphone type device, or even in sports when catching a ball.
What are the approaches used in thinning?
There are various algorithms to implement all these concepts:- 1) Zhang Suen Thinning algorithm. 2) Canny Edge detection. 3) Edge Based thinning algorithm. 4) Optimized iterative algorithm using successive erosion.
What is thinning in computer vision?
Thinning is a morphological operation that is used to remove selected foreground pixels from binary images, somewhat like erosion or opening. It can be used for several applications, but is particularly useful for skeletonization.
What do you mean by thickening and thinning?
In thinning the boundary of the object is subtracted from the object. For a image A and a Composite structuring element B=(B1,B2),Thinning can be defined as, AØB=A∩(A⊗B)C. Thickening: In Thickening a part of boundary of the background is added to the object.
