Research Article
SSL: A Novel Image Hashing Technique Using SIFT Keypoints with Saliency Detection and LBP Feature Extraction against Combinatorial Manipulations
Algorithm 2
Texture features extraction algorithm.
Input: Geometric information of keypoints | Output: Texture features around keypoints | (1) for to do | (2) Determine the th local region according to the geometric information of the th keypoint | (3) The pixels in the are denoted as | (4) // Calculate the LBP value [26] | (5) for to do | (6) Initialize a 8-bit vector | (7) Determine the neighbourhood pixels of , which are denoted as | (8) for to do | (9) if gray value of < gray value of then | (10) | (11) else | (12) | (13) end if | (14) end for | (15) Assign the vector to | (16) end for | (17) Convert vectors to decimal numbers | (18) Divide 0 to 255 into 32 intervals: | (19) Count the number of vectors in each interval as | (20) for to do | (21) if then | (22) | (23) else | (24) | (25) end if | (26) end for | (27) | (28) end for | (29) return Texture features |
|