Abstract

We present an optical technique for finding the centroids of nonoverlapping objects in a scene, thus locating the objects and preserving the underlying advantage of matched filtering approaches to pattern recognition. One is then free to extract any feature desired at these centroid locations rather than restricted to the matched filter test statistic. Furthermore, this allows general feature extraction avoiding prior scene segmentation into individual objects. The technique can also be used for tracking the motion of rigid or nonrigid objects. It consists of cross-correlating the input f(x,y) with a windowed version of the function x + iy and detecting the zeros of the magnitude of the resulting correlation. At these points the x and y first moments vanish. The window is selected based on the size and separation of the objects in a scene. Experimental verification as well as restrictions are also presented.

© 1987 Optical Society of America

Pattern recognition with generalized centroids and subcentroids

Shoude Chang and Chander P. Grover
Appl. Opt. 44(8) 1372-1380 (2005)

Accuracy of location measurement of a noisy target in a nonoverlapping background

Vitaly Kober and Juan Campos
J. Opt. Soc. Am. A 13(8) 1653-1666 (1996)

Optimal multichannel estimation of the location of a target with nonoverlapping noise

J. Campos, S. Lhostis, and M. Guillaume
J. Opt. Soc. Am. A 17(12) 2140-2147 (2000)

Centroid scale-space maps

Mark O. Freeman and Bahaa E. A. Saleh
J. Opt. Soc. Am. A 8(9) 1474-1487 (1991)

Detection of multiregion objects embedded in nonoverlapping noise

Javier García, Vincent Pagé, and Philippe Réfrégier
Opt. Lett. 26(18) 1394-1396 (2001)