The original LBP operator labels the pixels of an image with dec imal numbers, called LBP codes, which encode the local structure around each pixel [8, 25].
The LBP operator labels each pixel in the image by computing the sign of the differences between the central pixel and its neighboring pixels.
The Original LBP operator labels the pixels of an image by thresholding a 3×3 neighborhood of each pixel with the center value and considering the results as a binary number, of which the corresponding decimal number is used for labeling.
Basically, the operator labels a given pixel of an image by thresholding its neighbors in function of the pixel intensity and summing the thresholded values weighted by powers of two.
LBP operator labels each pixel of an image by thresholding its P neighbor's intensity values with the center value and converts the result into a pattern code by (1): LBP P, R x c, y c = ∑ p = 0 P − 1 s g p − g c 2 p, (1).
In the manual procedure, the operator labeled each identified spine with a marker labeled 'manual'manual
To overcome this difficulty, we introduce a novel notion of quantum Markov chain, especially suited for modelling quantum cryptographic protocols, in which quantum effects are encoded as super-operators labelling transitions, leaving the location information (nodes) being classical.
In order to do this, we utilized the dual MARCM method (Lai and Lee, 2006), which uses two independent binary expression systems (Gal4-UAS and LexA LexA operator) to label the MARCM clones.
The original LBP operator forms labels for the image pixels by thresholding the 3×3 neighbourhood with the center value and considering the result as a binary number.
The original LBP operator [10] labels the pixels of an image by thresholding a 3 × 3 neighborhood of each pixel with the center value and considering the results as a binary code.
