Automated visual quality evaluation of CVD film

This study describes the implementation and performance of a new image analysis algorithm, ALOET, as applied to automatically distinguishing between acceptable and unacceptable chemical vapor deposition (CVD) diamond film. ALOET is a texture feature which measures the homogeneity of the edge orientations in a local window, and which is useful in differentially characterizing large and small polycrystalline structures. The analysis in this study includes a performance metric for film quality evaluation, numerical and visual performance results, and an example analytical model for determining the algorithm's control parameters.

[1]  William G. Wee,et al.  Neighboring gray level dependence matrix for texture classification , 1982, Comput. Graph. Image Process..

[2]  C. S. G. Lee,et al.  Robotics: Control, Sensing, Vision, and Intelligence , 1987 .

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

[4]  A. R. Rao,et al.  A Taxonomy for Texture Description and Identification , 1990, Springer Series in Perception Engineering.

[5]  Larry S. Davis,et al.  Texture Analysis Using Generalized Co-Occurrence Matrices , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  K. Laws.  Textured Image Segmentation , 1980 .

[7]  Richard W. Conners,et al.  A Theoretical Comparison of Texture Algorithms , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Owen Robert Mitchell,et al.  Image segmentation using a local extrema texture measure , 1978, Pattern Recognit..