An improved block matching algorithm for motion estimation invideo sequences and application in robotics

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

Varietal Generation and Output

The substantive findings in Chapters 6–17 are synthesized and reviewed in this and the following chapter, which draw heavily on Walker et al., 2014. Findings are synthesized from two perspectives: a cross-sectional analysis across the 20 crops in 2009–2011 and a before-and-after comparison with the 1998 benchmark and the 2009–2011 data. Findings in this chapter are organized from the evaluation framework of inputs and outputs that was described in Chapter 3. Hypotheses from that chapter are revisited at the end of each thematic section. Where appropriate, results from South Asia reported in Chapters 13 and 14 are cited to provide a spatial benchmark for the outputs of data analysis in sub-Saharan Africa (SSA)..