Trainable COSFIRE filters for keypoint detection and pattern recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
George Azzopardi, Nicolai Petkov

Abstract

Keypoint detection is important for many computer vision applications. Existing methods suffer from insufficient selectivity regarding the shape properties of features and are vulnerable to contrast variations and to the presence of noise or texture. We propose a trainable filter which we call Combination Of Shifted FIlter REsponses (COSFIRE) and use for keypoint detection and pattern recognition. It is automatically configured to be selective for a local contour pattern specified by an example. The configuration comprises selecting given channels of a bank of Gabor filters and determining certain blur and shift parameters. A COSFIRE filter response is computed as the weighted geometric mean of the blurred and shifted responses of the selected Gabor filters. It shares similar properties with some shape-selective neurons in visual cortex, which provided inspiration for this work. We demonstrate the effectiveness of the proposed filters in three applications: the detection of retinal vascular bifurcations (DRIVE dataset: 98.50 percent recall, 96.09 percent precision), the recognition of handwritten digits (MNIST dataset: 99.48 percent correct classification), and the detection and recognition of traffic signs in complex scenes (1...Continue Reading

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Citations

Apr 25, 2012·Biological cybernetics·George Azzopardi, Nicolai Petkov
Mar 29, 2014·Biological cybernetics·Yun ZhangDelie Ming
Sep 23, 2014·Medical Image Analysis·George AzzopardiNicolai Petkov
Jul 3, 2015·Computers in Biology and Medicine·Wen-Bo ZhuQing-Lin Chen
Aug 16, 2014·Frontiers in Computational Neuroscience·George Azzopardi, Nicolai Petkov
Nov 28, 2018·PeerJ·Sufian A Badawi, Muhammad Moazam Fraz
Feb 7, 2021·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Dengqiang Jia, Xiahai Zhuang
May 29, 2021·Ultramicroscopy·B WiniarskiP J Withers
May 31, 2021·ISA Transactions·Hongzhen ZhuRui Zhao

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