An Efficient Randomized Algorithm for Detecting Circles

By T. Chen, K. Chung. Computer Vision and Image Understanding, 2001

334 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/9475c8031f251aff916222d9ac5da147ea6b056a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Sanchit Mahajan
2. Bidyut Baran Chaudhuri
3. Rishi Gupta
4. Priyanka Mukhopadhyay
5. Neha Kak
6. Atlas Collaboration

Citations in the corpus

• Iris Recognition System (2010, methodology): “[1][7] Firstly, an edge map is generated by calculating the first derivatives of intensity values in an eye image and then thresholding the result.”
• A survey of Hough Transform (2015, methodology): “Based on a parameter-free approach without using any accumulator arrays, the RCD method proposed in [126] first randomly samples four edge pixels of which three pixels are used to construct a possible circle, and the remaining one is used to confirm whether it can be promoted to a candidate circle…”