Update README.md

README.md

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 ## Overview
-This project focus on the detection and recognition of Euro banknotes and has the following associated paper:
+This project focus on the detection and recognition of Euro banknotes and has the following associated resources:
+
+- ICARSC 2016 paper: [Recognition of Banknotes in Multiple Perspectives Using Selective Feature Matching and Shape Analysis](https://www.researchgate.net/publication/301888929_Recognition_of_Banknotes_in_Multiple_Perspectives_Using_Selective_Feature_Matching_and_Shape_Analysis)
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+- [Presentation](https://www.researchgate.net/publication/301888713_Recognition-of-Banknotes-in-Multiple-Perspectives-Using-Selective-Feature-Matching-and-Shape-Analysis-Presentation)
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+- [Poster](https://www.researchgate.net/publication/301888902_Recognition-of-Banknotes-in-Multiple-Perspectives-Using-Selective-Feature-Matching-and-Shape-Analysis-Poster)
 
-[Multiview banknote recognition with component and shape analysis](https://www.researchgate.net/publication/260392128_Multiview_banknote_recognition_with_component_and_shape_analysis)
 
 **Abstract:**
-Robust banknote recognition in different perspective 
-views and in dynamic lighting conditions is a critical component in 
-assistive  systems  for  visually  impaired  people.  It  also  has  an 
-important  role  in  improving  the  security  of  ATM  maintenance 
-procedures  and  in  increasing  the  confidence  in  the  results
-computed by  automatic banknote counting machines.  Moreover, 
-with  the  proper  hardware,  it  can  be  an  effective  way  to  detect 
-counterfeit  banknotes.  With  these  applications  in  mind,  it  was 
-developed  a  system  that  can  recognize  multiple  banknotes  in 
-different perspective views and scales, even when they are part of 
-cluttered environments in which the lighting conditions may vary 
-considerably. The system is also able to recognize banknotes that 
-are partially visible, folded, wrinkled or even worn by usage.  To 
-accomplish  this  task,  the  system  is  based  in  image  processing 
-algorithms, such as feature detection, description and matching. 
-To improve the confidence in the recognition results, the contour 
-of the banknotes is computed using a homography, and its shape 
-is analyzed to make sure that it belongs to a banknote. The system 
-was  tested  with  82  test  images,  and  all  Euro  banknotes  were 
-successfully recognized, even when there were several  banknotes 
-in the same test image, and they were partially occluded.
+Reliable banknote recognition is critical for detecting counterfeit banknotes in ATMs and help visual impaired people. To solve this problem, it was implemented a computer vision system that can recognize multiple banknotes in different perspective views and scales, even when they are within cluttered environments in which the lighting conditions may vary considerably. The system is also able to recognize banknotes that are partially visible, folded, wrinkled or even worn by usage. To accomplish this task, the system relies on computer vision algorithms, such as image preprocessing, feature detection, description and matching. To improve the confidence of the banknote recognition the feature matching results are used to compute the contour of the banknotes using an homography that later on is validated using shape analysis algorithms. The system successfully recognized all Euro banknotes in 80 test images even when there were several overlapping banknotes in the same test image.
 
 ## Results
 
@@ -66,3 +53,9 @@ Fig. 5 - Detection of overlapping banknotes
 
 ## Building and developing
 The setup instructions on how to build and develop in Visual Studio is available [here](https://github.com/carlosmccosta/Currency-Recognition/blob/master/CurrencyRecognition/docs/Visual%20Studio%20configuration%20for%20OpenCV%202.4.8.txt)
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+## Related repositories
+- [ICARSC 2016 latex paper](https://github.com/carlosmccosta/Currency-Recognition-Article)
+- [ICARSC 2016 latex presentation](https://github.com/carlosmccosta/Currency-Recognition-Presentation)
+- [ICARSC 2016 latex poster](https://github.com/carlosmccosta/Currency-Recognition-Poster)