International Journal of Soft Computing
Abstract: This is a design approach of software on Image/pattern-recognition while eliminating the color /gray-code of an image for comparison. This approach is quite effective for both Black and White scenes or color scenes/images. Here we select particular part/parts of given image and we compare with the contents of database (image data). This approach will be the key idea for all the verification and identification system. Here the input is image (Black and White/Color) the output is a set of elements (pixels), we have various approaches they are Minterm (minimized term) Extraction for black/white image analysis for handling various gray levels through variables like A, B, C, D,� like wise, White pixels can be maintained through their inverse ie 
..., Respectively and Maxterm Extraction for color images for handling the RGB (Red, Green, Blue and Colors) through nested minterm extraction and it is opt to handle various color-gray levels the variables like R1, R2, R3,R4,. color Green is processed through G1, G2, G3, G4 and color Red is processed through R1, R2, R3, R4 and color Blue is processed through B1, B2, B3, B4.
How to cite this article:
K. Selvam and B. Poorna , 2008. Image (B and W, Color) Extraction Approach Wide Quine Mc Cluskey�s Tabular Method . International Journal of Soft Computing, 3: 167-171.