Algorithm 1: Proposed WFBT-SBP RGB-D Texture Descriptor

Input: The set of images of dataset
Description: The images are processed with WFBT-SBP Algorithm to obtain the texture descriptors of images of dataset.
Step 1:	Split RGB image into different components like Red, Green and Blue.
	Solve 1.1: Solve (1)
Step 2:	Initialization
	$R_i=X_{j,k}{G}_i=Y_{j,k}{B}_i=Z_{j,k}$
Step 3:	Conversion from decimal values to binarized values of R, G, B
	Step 3.1: Solve (5) to obtain X
	Step 3.2: Solve (6) to obtain B.
	Step 3.3: Solve (7) to get Xj,k.
	Step 3.4: Repeat 2.1 to 2.3 to convert decimal to binary
Step 4:	[If there is a pattern match, assign weights and summate the matched patterns]
	Step 4.1: Solve (8) to compare patterns $P_{i,j}^q$of central pixel with 8-nearest neighbors.
	for q = 1: n $if{P}_{i,j}^q==1$ $P_{i,j}^q=2^j$ $W_q=\sum _{j=1}^8\sum _{i=1}^8{P}_{i,j}^q$ End End
Step 5:	Obtain WFBT-SBP in the form of Xj,k
Step 6:	Repeat Step 3 to 5 for Green component to obtain$Y_{j,k}$.
Step 7:	Repeat Step 3 to 5 for Blue component to obtain Zj,k.
Step 8:	Combine the result of Step 5, Step 6 and Step 7.
Output: Weighted FBT-SBP of an image.