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СÃõÚÒ»´ÎͶ¸åÍâÎÄÆÚ¿¯ lElsvier ÆìÏ嵀 image and vesion computing,ÀúʱÁù¸öÔ£¬ÊÕµ½±à¼­µÄ»ØÐÅÈçÏ£º¸Ð¾õµÚÒ»¸öreviewerÒâ¼û±È½Ï¿Ï¶¨£¬µ«Êǵڶþ¸öreviewer
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We have received reports from the Referees who were asked to review your manuscript.  Please find the relevant parts of each review attached to this email.

If you decide to submit a revised version of your manuscript, we would ask you to provide a written statement of the way you have taken account of the referee comments in preparing the revision.  You may include the text of this statement at the beginning of the manuscript text when you submit the revised manuscript.  (It can be separated at a later stage).  

We will return the revised manuscript to the reviewers for further comment and we may send the manuscript to additional reviewers before reaching a final decision about publication. Please submit your revision by the Sep 04, 2009.

For your guidance, reviewers' comments are appended below.

To submit a revision, go to http://ees.elsevier.com/imavis/ and log in as an Author.  You will see a menu item call Submission Needing Revision.  You will find your submission record there.

Yours sincerely

Maja Pantic, PhD
Editor in Chief
Image and Vision Computing




Reviewers' comments:

Reviewer #1: * The paper presents a new approach for lane identification based on an quadratic parabola model and the ant colony algorithm.

In my opinion the contents is interesting, but the presentation should really be improved in order to increase readability.

* English really needs to be improved (some parts can hardly be understood)
  - also use common terms (e.g. pretreatment -> preprocessing), ...

Detailed comments to the contents:

* p.7: "lower filter ist applied..." -> lowpass filter

* p.9, eq. (9) & (10):
  - For me, it is not obvious how the objective function F(a,b,c) depends on a and c. Please explain.
  - Parameters  and  depend on image and environmental conditions and are chosen by experiments. Please try to present all these results in a more compact/uniform way (table?) and derive final results on p.11 from it (-> table?)
  
* p.12, sec.4: "The ant colony algorithm posed by Dorigo" => add reference [M. Dorigo: optmization, Learning, and Natural Algorithms, PhD thesis, Policenico di Milano, Italie, 1992.]

* p.12, sec.4: Please add a structogram to illustrate the overall algorithm.

* p.13: How did you choose a1, b1 and c1 in eq. (11) for the first image (initial ROI)? Please explain.

* p.16, sec. 5: You just mention results in fig. 12-15. For how many images / image sequences did you test your method? Did it always work? What are the limits?

* p.17, sec. 6: What do you mean be "excellent real-time"? Please mention hardware used, image size and frames per second.




Reviewer #2: Please check the English and re-submit for review.
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