Image structural information assessment

Many image information assessment techniques have been proposed in the past. Most of them are based on the image histogram. When the histogram of an image is derived, the structural component of the image is generally ignored. The information assessed using the histogram is thus independent of the image spatial attributes. In this investigation an original computational technique for the assessment of the structural information content of an image is described. The developed technique produces as output an information measure which is proportional to the image geometrical attributes such as the size, the shape complexity, etc. The technique is normalised and tested on a series of artificial images. The results obtained are analysed to show how the normalised information is related to the image geometrical attributes. The results obtained are also confirmed when English character images are considered. Finally, conclusions will be drawn in terms of the suitability of the technique for applications in computer imaging problems.

[1]  A. D. Brink,et al.  Using spatial information as an aid to maximum entropy image threshold selection , 1996, Pattern Recognit. Lett..

[2]  Petros Maragos,et al.  Pattern Spectrum and Multiscale Shape Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  W. T. Grandy Maximum entropy in action: Buck, Brian and Macaulay, Vincent A., 1991, 220 pp., Clarendon Press, Oxford, £30 pb, ISBN 0-19-8539630 , 1995 .

[4]  Ramón Román Roldán,et al.  Multiresolution-information analysis for images , 1991 .

[5]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[6]  Mohammad F. Daemi,et al.  Recognition information , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[7]  G. Awcock,et al.  Applied Image Processing , 1995 .

[8]  Petros Maragos Pattern spectrum of images and morphological shape-size complexity , 1987, ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Mohammad Farhang Daemi,et al.  Rotational information in shape description , 1996, Optics & Photonics.

[10]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[11]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[12]  Roger J. Clarke Image coding and the coding standards , 1997 .

[13]  Ahmed S. Abutableb Automatic thresholding of gray-level pictures using two-dimensional entropy , 1989 .

[14]  Bruce G. Batchelor,et al.  Pattern Recognition: Ideas in Practice , 1978 .