Paper: 340024
Title: Pattern recognition with adaptive morphological composite filters

-------------------- review 1 --------------------
---------------------------- REVIEW 1 --------------------------
PAPER: 4
TITLE: Pattern recognition with adaptive morphological composite filters
 
OVERALL RATING: 1 (weak accept) 
REVIEWER'S CONFIDENCE: 3 (high) 
Relevance to this conference: 4 (good)
Originality/Uniqueness: 3 (fair)
English readability: 4 (good)
Paper organization/presentation: 3 (fair)
Has good survey been done?: 1 (very poor)


The article presents an application of adaptive correlation filters used to remove the background noise to increase pattern recognition capabilities. It contains the results of experiments over object recognition by the background removal.

The article misses the-state-of-the-art section. It contains few citations, but they do not address already existing applications of correlation filters only mention three kinds of filtering algorithms. The reference section if very limited, it should contain more positions, proving that a detailed survey was done.

It would be easier for reader to understand section 2 if author provide a picture presenting the idea of a moving window (the first paragraph in this section). The equations should be centred.

The figure 2 shows the objects to be recognised and background to be removed. In my opinion this section misses an example of noisy image and filter output i.e. pre-processed image. It would make easier to understand the example by seeing the  images being filter's income and outcome. Moreover, it would be more simulative to show another test case so reader could evaluate filters comparing the results achieved for the two images. Currently it is questionable how the results were influenced by the selection of filters and how by the selection of the test image. 



-------------------- review 2 --------------------
---------------------------- REVIEW 2 --------------------------
PAPER: 4
TITLE: Pattern recognition with adaptive morphological composite filters
 
OVERALL RATING: 2 (accept) 
REVIEWER'S CONFIDENCE: 3 (high) 
Relevance to this conference: 3 (fair)
Originality/Uniqueness: 3 (fair)
English readability: 4 (good)
Paper organization/presentation: 4 (good)
Has good survey been done?: 4 (good)


Authors propose and design adaptive morphological composite correlation filters for robust and distortion-invariant pattern recognition. 
The recognition performance of the proposed filters is evaluated and computer simulation results are provided and discussed.  
In general, the authors cover the overall subject in a critical way.  The paper  is well presented and organised.
I believe that the paper  is comprehensive, original and  would  be important  to researchers within the pattern recognition field.

Therefore, I suggest to be accepted. 



-------------------- review 3 --------------------
---------------------------- REVIEW 3 --------------------------
PAPER: 4
TITLE: Pattern recognition with adaptive morphological composite filters
 
OVERALL RATING: 2 (accept) 
REVIEWER'S CONFIDENCE: 3 (high) 
Relevance to this conference: 3 (fair)
Originality/Uniqueness: 4 (good)
English readability: 4 (good)
Paper organization/presentation: 3 (fair)
Has good survey been done?: 3 (fair)


In this paper, the design of adaptive morphological composite correlation filters for robust pattern recognition is presented in detail.
Furthermore, the authors evaluate the performance of the proposed filters in a very critical way. 
Computer simulation results are also presented in a detail way.  
I believe, that  the presented work  is original  and  novel. The paper is well organised. 
The proposed method would be very interesting to conferences attendees.

Concluding, I suggest to be accepted as it is.