Improved Hough Transform and Total Variation Algorithms for Features Extraction of Wood
Round 1
Reviewer 1 Report
This paper presents a new model by suing the total variation algorithm and the improved Hough transform. The new model can save time and extract features of wood from the indoor and outdoor images of wood, and the image noises can be removed from the indoor wood images of the unprocessed low-noise logs. The scheme of this paper is logical. The reasonable methods are used to develop the model. This is an interesting paper that is technically rigorous, and correct in the conclusions that it reaches. The outcomes from tis paper are useful for applications. On the other hand, there are points that deserve attention, which might improve the paper.
Words in line 71-81 are unnecessary because steps to identify the features of wood ring are shown in Figure 1 and the descriptions are made in section 2.1-2.4
The authors made discussion about the back ground of the outdoor images and the human errors for classifying wood images into the low-noise images and high-noise images (line 287- 296. I have the following two questions for the authors.
How big are the effects of the background and the human errors on identifying the parameters of wood ring obtained from the model?
Is it possible to reduce the human errors or to classify the wood images using a computer-based method?
There are writing mistakes. Below are some of the mistakes and suggestions for correcting them.
Line 64-65 The proposal can further improve the accuracy of judging the wood quality
based on features of wood annual rings from our proposal.
The model presented in this paper can further improve the accuracy of judging the wood quality based on features of wood annual rings.
Line 72-73 The process is show in Figure 1.
The process is shown in figure 1,
Line 128 The express is showed
The express is shown
Line 160 The wood always has noise caused from wormholes or coarse surface.
The images of wood always have image noise due to wormholes or coarse surface.
Line 289-290 The background might affect the effect of the TV algorithm for removing the noise.
The background might affect TV algorithm for removing the noise.
Line 301 the each ring width is
each of the ring widths is
Line 303-305 In future studies, it can explore that whether the consideration of thickness of annual ring can bring better results.
In future studies, it will explore whether the consideration of thickness of annual rings can bring better results.
Author Response
Please see the attachment
Reviewer 2 Report
Review
Improved Hough Transform and Total Variation Algorithms for Features Extraction of Wood
The results of this research are original, significant, well defined and all conclusions are justified and supported by the results.
The authors have addressed an important question with similar themes and conducted pre-research of a similar subject.
The paper presents original research work and provides an advance in current knowledge in computer scanning of wood and feature extraction from wood images.
The paper is written in an appropriate way, all the data and analyses are presented appropriately.
The main subject of the paper was to make a new model for accurate wood ring recognition and use it to save time for human work.
This paper proposes a new model combining the improved Hough transform and the total variation (TV) algorithm for features extraction automatically from wood images, such as the number of rings, the width of annual rings, and the average width of the 15th ring from the center and outside.
The results show that the new model can clearly extract the edge of wood annual rings and calculate the related parameters from the indoor wood images of the processed logs and the unprocessed low-noise logs.
This paper provides an advance towards the current knowledge in computer scanning and wood ring recognition, the conclusions are interesting for the readership of the Journal and will attract a wide readership not only in the field of the wood industry.
The English language is understandable but needs some corrections that are given in the review.
Comments for author File: 
Comments.pdf
Author Response
Thank you for your kind comments.
Revised as requested. (in yellow)
