For illustration, we display the binary pattern of ring (r = 2).
Figure 3 Example of binary pattern run length matrices.
In order to make this system robust in terms of illumination, a Binary Pattern Run Length matrix was employed; this matrix is combination of Binary Pattern and a Run Length matrix.
Second, construct the Run Length matrices from the binary patterns in a direction 0°. Figure 3 shows an example of a Binary Pattern Run Length matrix using LBP operator.
In order to make this method robust in terms of illumination, the Binary Pattern Run Length matrix was employed; this matrix is the combination of a Binary Pattern and a Run Length matrix.
Further, 57 binary patterns of the possible 64 (2 6) patterns were used to label each Pfam domain with 1,641 domains present in all the genomes (ie, Pfam domains with binary pattern '111111') (Table 2).
Our binary tests ϕf, r, s, τ, type (I) are defined as: f BPRLM r − f BPRLM s > τ, (8 where f is the statistical texture feature, r and s are pixel coordinate, τ is a threshold, θ is the direction, type is the type of Binary Pattern, and BPRLM r) is the Binary Pattern Run Length Matrix (BPRLM) at gray level I(r).
In order to extract feature of training patch, we calculate statistical texture features from the Binary Pattern Run Length matrix.
The binary pattern run length matrix is proposed for binary test.
The Binary Pattern Run Length Matrix is the combination between the Binary Pattern and Run Length matrix, which can be calculated by the following steps.
