Directional descriptors using zernike moment phases for object orientation estimation in underwater sonar images

Conventional methods for rotation angle estimation are not very robust to variations in object shape or intensity. However in real object recognition scenarios like in underwater sonar images, the object seldom retains the same appearance in different test cases. Object representation using Zernike moments allows to capture these variabilities in a way that makes it robust in the context of rotation angle estimation. This paper presents a novel way to exploit the phase information of Zernike moments to infer the object orientation. This is achieved via a compact directional representation that describes the variation in object shape along different directions. Results yielded on the DIDSON sonar imageset collected by CSAIL at MIT show that the method can robustly infer the relative orientation between objects.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Naveen Kumar, Adam C. Lammert, Brendan Englot, Franz S. Hover, Shrikanth S. Narayanan
• Keywords: ICASSP 2011, Object Recognition Scenarios, Object Shape, Rotation Angle Estimation, Signal Processing