Black White Color and Gray Pixel Extraction Model
Abstract
This is a design approach of software on image and pattern recognition, while eliminating the color and gray code of an image for comparison. This approach is quite effective for black and white and color images or scenes. Here we select particular part or parts of a given image and we compare with the contents of template-image (biometric) database. This approach will be the key idea for all the verifications and identification systems of Automated Biometric Analysis. Here the input is image (black and white or color) the output is a set of picture elements (pixels), we have various approaches they are (1) Minterm (minimized term) extraction for black and white image analysis and handling various gray levels through variables like A, B, C, D and the inverse (negative) image of the same with corresponding gray levels can also be maintained by their inverse like A', B',C',D'...respectively. (2) Maxterm (maximized term) the color images are generated by three primary colors (Red, Green, Blue) and this image can be recognized by both Minterm and Maxterm approaches and consider any one of the primary colors through Minterm approach and various gray levels of the primary color can be identified and analyzed by variables like A, B, C, D and the inverse (negative)image gray-levels can be performed by A',B',C',D',...respectively. Further the remaining two primary colors will be treated by the inverse of the earlier function of selected primary color (but not by the inverse variables) i.e., (A, B, C, D,) of primary color approach (maxterm approach).
DOI: https://doi.org/10.3844/jcssp.2007.914.917
Copyright: © 2007 K. Selvam and B. Poorna. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Prime implicant
- sum of products
- gray
- minterm
- probabilistic determination