Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fourier descriptors (FD's) are widely used shape descriptors. By first warping the scanning speed of the contour before calculating the FD's, the shape approximation can be improved. This approach has never been properly tested on real applications.   compare these new shape descriptors to the regular FD's. A database of over 400 leaf shapes is approximated using these shape descriptors and compared to the approximation based on FD's. The error of the approximation was measured with the Hausdorff distance and modified Hausdorff distance, resulting for both criteria in an average improvement of more than 10% over approximation based on FD's.
['Jonas De Vylder', 'Wilfried Philips']
I am writing a research paper on a idea 2-D shape representation using improved Fourier descriptors
[{"from": "human", "value": "I am writing a research paper on a idea 2-D shape representation using improved Fourier descriptors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fourier descriptors (FD's) are widely used shape descriptors. By first warping the scanning speed of the contour before calculating the FD's, the shape approximation can be improved. This approach has never been properly tested on real applications.   compare these new shape descriptors to the regular FD's. A database of over 400 leaf shapes is approximated using these shape descriptors and compared to the approximation based on FD's. The error of the approximation was measured with the Hausdorff distance and modified Hausdorff distance, resulting for both criteria in an average improvement of more than 10% over approximation based on FD's."}]