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Shape Recognition with Fourier Descriptors and General Shape Features

Data:

  • Training: There are three different classes of object shapes: triangular shapes (../images/img1.jpg), quadrangular shapes (../images/img2.jpg) and pentagon (../images/img2.jpg) shapes. Each of the three shape classes has 10 samples.
  • Testing: (../images/img4.jpg) 15 objects from all of the above mentioned three classes

Preprocessing:

  1. Thresholding and pre-processing: generate binary images
  2. Connected component labeling and fragment removal
  3. Boundary tracing

Feature Extraction:

  • Computing Fourier Descriptors
  • Alternative: 6 different general shape features: compactness, rectangularity, circularity, eccentricity, area/perimiter, etc. (General shape features are not robust a lot but it is not bad for classifying simple shapes such as triangular, pentagons, etc.)

Classifiers:

  • Nearest-mean classification

Results:

fd

shape-features

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