Publications

@article{garcia-ordas_azibo_2014,

title = {aZIBO: a new descriptor based in shape moments and rotational invariant features},

author = {Marïa Teresa García-Ordás and Enrique Alegre and Víctor González-Castro and Diego García-Ordás},

url = {https://ieeexplore.ieee.org/abstract/document/6977127},

year  = {2014},

date = {2014-01-01},

journal = {2014 22nd International Conference on Pattern Recognition},

pages = {2395–2400},

abstract = {This work introduces a new shape descriptor called ZIBO (absolute Zernike moments with Invariant Boundary Orientation), combining global Zernike moments and a rotationally invariant version of the Edge Gradient Co-occurrence Matrix (EGCM). The descriptors were applied to three datasets (Kimia99, MPEG2, MPEG7) and evaluated using kNN with City block and Chi-square distance metrics. The combination of global and local descriptors achieved better results than the baseline ZMEG method. Specifically, the ZIBO descriptor obtained success rates of 78.29% on MPEG7 and 81.00% on MPEG2, outperforming ZMEG by 2.43% and 3.75%, respectively.},

note = {Publisher: IEEE},

keywords = {EGCM, Image classification, machile learning, shape descriptors, zernike moments},

pubstate = {published},

tppubtype = {article}

}