A Segment-Based Algorithm for Grid Junction Corner Detection Used in Stereo Microscope Camera Calibration

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript gives an algorithm for detecting grid corners based on image segmentation for stereo microscope camera calibration, where approximate quadrangle is outlined by image processing of the original grid pattern and coordinates are given at the sub-pixel level by model fitting. The experimental results show that the method given in the manuscript has high accuracy. However, there are still some problems.

Q1:  What is the difference between using convolutional operations and using contrast enhancement techniques such as histogram equalization?

Q2: The implementation of the subsequent algorithms in this manuscript is based on the pre-existing image segmentation, so how is the criterion for setting the threshold determined in the thresholding process in Fig. 2(e)?

Q3: According to the measurement results in Table I, why is the proposed algorithm in this paper less effective under ideal conditions?

Q4: Please add the results of experiments using OpenCV in the reprojection error experiments in Table 2.

 

Comments on the Quality of English Language

There are some minor grammatical errors in the text, e.g., "by measure" should be replaced by "by measuring"; the author should double-check.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

 

1.    Remove ‘—’ in lines 1, 53, and 54.

2.    The introduction needs improvements by adding new papers.

3.    Please highlight the novelty of the paper in the Introduction.

4.    Add the workflow of the other sections at the end of Introduction section.

5.    Since it is mentioned that the GESeF algorithm has three procedures, it can be better to specify them in Figure 1.

6.    Did you apply the proposed method for other applications such as object recognition, image matching?

7.    In line 162, it is written that if theta_1 and theta_2 are known; can you explain the case they are unknown? What is the minimum and maximum of theta_1 and theta_2? If possible add an example.

8.    Subsection 2.3(2.3.1 and 2.3.2) is not clear, please add more information.

9.    The Conclusion section needs to be extended and improved by highlighting the main results, the limitations of the method, and mentioning additional applications of the considered method which can be useful for readers.

Comments on the Quality of English Language

Minor editing of English language required.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf