DocumentCode
3239229
Title
Phase Invariant Keypoint Detection
Author
Bharath, Anil Anthony ; Kingsbury, Nick
Author_Institution
Imperial Coll. London, London
fYear
2007
fDate
1-4 July 2007
Firstpage
447
Lastpage
450
Abstract
This paper introduces extensions to the complex wavelet keypoint detection paper [1], Keypoints are generated by finding local peaks in accumulated, interpolated maps of the product of magnitudes of directional complex filter responses, as in earlier work. Gradient vector fields derived from these maps are used for keypoint scale characterisation, but this is now performed so as to remove the directionality of gradient field sampling, thereby improving the stability of scale estimates. A new class of keypoints is also introduced: the circular measure (CM) keypoints, which are used to augment the locations found by the filter magnitude product (FMP) keypoints. This new keypoint class generates a higher proportion of keypoints in the interiors of objects, whilst simultaneously providing approximate object scale information, and appears appropriate for directing the attention of a vision system to the interiors of well-defined regions.
Keywords
filtering theory; gradient methods; image sampling; interpolation; object detection; directional complex filter; filter magnitude product; gradient field sampling; phase invariant keypoint detection; Biomedical engineering; Educational institutions; Filtering; Filters; Frequency; Image processing; Phase detection; Robustness; Solids; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Signal Processing, 2007 15th International Conference on
Conference_Location
Cardiff
Print_ISBN
1-4244-0882-2
Electronic_ISBN
1-4244-0882-2
Type
conf
DOI
10.1109/ICDSP.2007.4288615
Filename
4288615
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