Illumination-invariant pattern recognition with joint-transform-correlator-based morphological correlation.

The performance of nonlinear morphological correlation is investigated and compared with that of conventional linear correlation. In particular, the effects of illumination variations on the morphological correlation output are investigated in detail. The morphological correlation is shown to be invariant to uniform input-image illumination when the input-image illumination is higher than that of the reference. It also provides higher pattern discriminability, sharper peaks, and more-robust detection in the presence of salt-and-pepper noise than does the linear correlation. Computer-simulation results are provided.

[1]  James C. Kirsch,et al.  Illumination-independent high-efficiency joint transform correlator. , 1991, Applied optics.

[2]  Francis T. S. Yu,et al.  A real-time programmable joint transform correlator , 1984 .

[3]  A. B. Vander Lugt,et al.  Signal detection by complex spatial filtering , 1964, IEEE Trans. Inf. Theory.

[4]  F T Yu,et al.  Performance of a phase-transformed input joint transform correlator. , 1996, Applied optics.

[5]  B. Javidi,et al.  Binary nonlinear joint transform correlation with median and subset median thresholding. , 1991, Applied optics.

[6]  J. Goodman,et al.  A technique for optically convolving two functions. , 1966, Applied optics.

[7]  J García,et al.  Nonlinear morphological correlation: optoelectronic implementation. , 1998, Applied optics.

[8]  M A Karim,et al.  Fringe-adjusted joint transform correlation. , 1993, Applied optics.

[9]  J L Horner,et al.  Pattern recognition with binary phase-only filters. , 1985, Applied optics.

[10]  T J Grycewicz,et al.  Fourier-plane windowing in the binary joint transform correlator for multiple target detection. , 1995, Applied optics.

[11]  B. Kumar,et al.  Performance measures for correlation filters. , 1990, Applied optics.

[12]  R K Wang,et al.  Modified fringe-adjusted joint transform correlation to accommodate noise in the input scene. , 1996, Applied optics.

[13]  J P Allebach,et al.  Optical median filtering using threshold decomposition. , 1987, Applied optics.

[14]  L A Romero,et al.  Normalized correlation for pattern recognition. , 1991, Optics letters.

[15]  Edward J. Coyle,et al.  Stack filters , 1986, IEEE Trans. Acoust. Speech Signal Process..

[16]  Petros Maragos,et al.  Optimal Morphological Approaches To Image Matching And Object Detection , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[17]  G. S. Pati,et al.  Illumination sensitivity of joint transform correlators using differential processing: computer simulation and experimental studies , 1998 .

[18]  D Mendlovic,et al.  Modified morphological correlation based on bit-map representations. , 1999, Applied optics.

[19]  Bahram Javidi,et al.  Binary nonlinear joint transform correlator performance with different thresholding methods under unknown illumination conditions. , 1995, Applied optics.

[20]  M S Alam,et al.  Joint-transform correlation under varying illumination. , 1993, Applied optics.

[21]  Kehar Singh,et al.  Experimental and simulation studies on the performance of binary and gray-valued joint transform correlators under poor illumination conditions and nonoverlapping background noise , 1997 .