TY - JOUR
T1 - An improved block matching algorithm for motion estimation in video sequences and application in robotics
AU - Bhattacharjee, Kamanasish
AU - Kumar, Sushil
AU - Pandey, Hari Mohan
AU - Pandey, Hari Mohan
AU - Pant, Millie
AU - Windridge, David
AU - Chaudhary, Ankit
N1 - Bhattacharjee, Kamanasish , Kumar, Sushil , Pandey, Hari Mohan , Pant, Millie , Windridge, David Chaudhary, Ankit (2018)ORCID: https://orcid.org/0000-0001-5507-8516 and An improved block matching algorithm for motion estimation in video sequences and application in robotics. Computers Electrical Engineering, 68 . pp. 92-106.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms.
AB - Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms.
KW - Block matching
KW - Differential evolution
KW - Harmony search
KW - Robotics Motion estimation
KW - Video compression
UR - http://eprints.mdx.ac.uk/24030/
UR - https://www.sciencedirect.com/science/article/abs/pii/S0045790617311928
U2 - 10.1016/j.compeleceng.2018.03.045
DO - 10.1016/j.compeleceng.2018.03.045
M3 - Article
VL - 68
JO - Computers Electrical Engineering
JF - Computers Electrical Engineering
ER -