TY - GEN
T1 - Wavelet-based circular hough transform and its application in embryo development analysis
AU - Cicconet, Marcelo
AU - Geiger, Davi
AU - Gunsalus, Kris
PY - 2013
Y1 - 2013
N2 - Detecting object shapes from images remains a challenging problem in computer vision, especially in cases where some a priori knowledge of the shape of the objects of interest exists (such as circle-like shapes) and/or multiple object shapes overlap. This problem is important in the field of biology, particularly in the area of early-embryo development, where the dynamics is given by a set of cells (nearly-circular shapes) that overlap and eventually divide. We propose an approach to this problem that relies mainly on a variation of the circular Hough Transform where votes are weighted by wavelet kernels, and a fine-tuning stage based on dynamic programming. The wavelet-based circular Hough transform can be seen as a geometric-driven pulling mechanism in a set of convolved images, thus having important connections with well-stablished machine learning methods such as convolution networks.
AB - Detecting object shapes from images remains a challenging problem in computer vision, especially in cases where some a priori knowledge of the shape of the objects of interest exists (such as circle-like shapes) and/or multiple object shapes overlap. This problem is important in the field of biology, particularly in the area of early-embryo development, where the dynamics is given by a set of cells (nearly-circular shapes) that overlap and eventually divide. We propose an approach to this problem that relies mainly on a variation of the circular Hough Transform where votes are weighted by wavelet kernels, and a fine-tuning stage based on dynamic programming. The wavelet-based circular Hough transform can be seen as a geometric-driven pulling mechanism in a set of convolved images, thus having important connections with well-stablished machine learning methods such as convolution networks.
KW - Biological cells
KW - Circular hough transform
KW - Machine vision
UR - http://www.scopus.com/inward/record.url?scp=84878233243&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878233243&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84878233243
SN - 9789898565471
T3 - VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
SP - 669
EP - 674
BT - VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
T2 - 8th International Conference on Computer Vision Theory and Applications, VISAPP 2013
Y2 - 21 February 2013 through 24 February 2013
ER -