Identify credit card shape using machine learning












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I have to approach this task : identify credit card from a image. I am attaching example image below



enter image description here



I have to identify and localize credit card from this image. The real challenge is that the card can be placed on any background and the color of card can change based on the company it belongs to.



In order to solve this task I tried using tensor flow object detection api the downside of this api is it fails to recognize cards which are not in its training data set.



My problem here is I am not concerned with the color of card or what information the card has. I am only concerned about finding the outline of card in an image and isolating the outline of card from rest of the image.



Is there a way using ML/CNN to do this. I tried OpenCV approaches to detect contours but even this approach fails when there is lot of text or other noise in the cards background.









share









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    0












    $begingroup$


    I have to approach this task : identify credit card from a image. I am attaching example image below



    enter image description here



    I have to identify and localize credit card from this image. The real challenge is that the card can be placed on any background and the color of card can change based on the company it belongs to.



    In order to solve this task I tried using tensor flow object detection api the downside of this api is it fails to recognize cards which are not in its training data set.



    My problem here is I am not concerned with the color of card or what information the card has. I am only concerned about finding the outline of card in an image and isolating the outline of card from rest of the image.



    Is there a way using ML/CNN to do this. I tried OpenCV approaches to detect contours but even this approach fails when there is lot of text or other noise in the cards background.









    share









    $endgroup$















      0












      0








      0





      $begingroup$


      I have to approach this task : identify credit card from a image. I am attaching example image below



      enter image description here



      I have to identify and localize credit card from this image. The real challenge is that the card can be placed on any background and the color of card can change based on the company it belongs to.



      In order to solve this task I tried using tensor flow object detection api the downside of this api is it fails to recognize cards which are not in its training data set.



      My problem here is I am not concerned with the color of card or what information the card has. I am only concerned about finding the outline of card in an image and isolating the outline of card from rest of the image.



      Is there a way using ML/CNN to do this. I tried OpenCV approaches to detect contours but even this approach fails when there is lot of text or other noise in the cards background.









      share









      $endgroup$




      I have to approach this task : identify credit card from a image. I am attaching example image below



      enter image description here



      I have to identify and localize credit card from this image. The real challenge is that the card can be placed on any background and the color of card can change based on the company it belongs to.



      In order to solve this task I tried using tensor flow object detection api the downside of this api is it fails to recognize cards which are not in its training data set.



      My problem here is I am not concerned with the color of card or what information the card has. I am only concerned about finding the outline of card in an image and isolating the outline of card from rest of the image.



      Is there a way using ML/CNN to do this. I tried OpenCV approaches to detect contours but even this approach fails when there is lot of text or other noise in the cards background.







      machine-learning python cnn opencv





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