Combined local color and texture analysis of stained cells

Abstract Combined color and texture techniques provide new, useful features for blood cell analysis. After scene segmentation, texture line following programs define the borders of textons, the smallest texture grains. Size, color, and shape features are then calculated for each texton. The final feature data set includes: (1) The nucleus and cytoplasm features: size and shape, measurements of the texture lines from the green TV image, average CIE-PAL color coordinates and a color code. (2) The new texton features: total number of texton pixels with a specific color code, mean texton radius, size for each color code, and texton shape factors.

[1]  H M Aus,et al.  Comparative colorimetry in cytophotometric measurements of azure B-eosin Y-stained and Giemsa-stained blood cell smears. , 1982, Analytical and quantitative cytology.

[2]  C. Garbay.  A Color Metric As A Tool For Cytologic Image Analysis , 1982, Other Conferences.

[3]  Harry Harms.  Neue Verfahren in der Bildverarbeitung, insbesondere in der lichtmikroskopischen Zellbildklassifizierung , 1982 .

[4]  Raj Reddy,et al.  Change Detection and Analysis in Multispectral Images , 1977, IJCAI.

[5]  H M Aus,et al.  Estimation of sampling errors in a high-resolution TV microscope image-processing system. , 1984, Cytometry.

[6]  Azriel Rosenfeld,et al.  A Comparative Study of Texture Measures for Terrain Classification , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[8]  Larry S. Davis,et al.  An Empirical Evaluation of Generalized Cooccurrence Matrices , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Azriel Rosenfeld,et al.  Digital Picture Processing, Volume 1 , 1982 .

[10]  Olivier D. Faugeras,et al.  Visual Discrimination of Stochastic Texture Fields , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[12]  Ernest L. Hall,et al.  Computer Image Processing and Recognition , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  B. Julesz.  Textons, the elements of texture perception, and their interactions , 1981, Nature.

[14]  H. Harms,et al.  Computer aided analysis of chromatin network and basophil color for differentiation of mononuclear peripheral blood cells. , 1979, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[15]  A V Kulkarni.  Effectiveness of feature groups for automated pairwise leukocyte class discrimination. , 1979, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[16]  Azriel Rosenfeld,et al.  Digital Picture Processing , 1976 .

[17]  A. Rosenfeld,et al.  Edge-Based Texture Measures. , 1981 .