文件名称:DETECTION-AND-DECODING-OF-QR-CODE
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This an OPENCV based project. Here we are implementing the algorithm that uses adaptive
methods to segment the image to identify objects.
The objects are then used to form candidate markers which are examined for several criteria.
Potential markers are then sampled and guide information present in the marker is used to verify
the data. The algorithm is invariant to scale and rotation and is robust to motion blur and varying
illumination.-This is an OPENCV based project. Here we are implementing the algorithm that uses adaptive
methods to segment the image to identify objects.
The objects are then used to form candidate markers which are examined for several criteria.
Potential markers are then sampled and guide information present in the marker is used to verify
the data. The algorithm is invariant to scale and rotation and is robust to motion blur and varying
illumination.
methods to segment the image to identify objects.
The objects are then used to form candidate markers which are examined for several criteria.
Potential markers are then sampled and guide information present in the marker is used to verify
the data. The algorithm is invariant to scale and rotation and is robust to motion blur and varying
illumination.-This is an OPENCV based project. Here we are implementing the algorithm that uses adaptive
methods to segment the image to identify objects.
The objects are then used to form candidate markers which are examined for several criteria.
Potential markers are then sampled and guide information present in the marker is used to verify
the data. The algorithm is invariant to scale and rotation and is robust to motion blur and varying
illumination.
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DETECTION AND DECODING OF QR CODE.pdf