Performance Analysis of Multi-Level HAAR in Background Removal for Object Detection

Objective: This study proposes performance improvement in speed of multi-level HAAR processed images for object detection. Method: Background subtraction algorithm is implemented using phase as a feature to reduce illumination variation. The algorithm is implemented on level 2 and level 3 HAAR compressed images. Simulation results are obtained on kit ware database. Findings: Simulation results show that object detection is faster in level 3 HAAR compressed images as compared to level 2 and level 1 HAAR compressed images. Average time required for processing single frame is in range of 6.53 to 29.22 ms in level 3 while that in level 2 is 6.65 to 36.46 ms. Improvement: Using this approach saving of 5% to 22% of processing time is observed at level 2 of HAAR while a saving of 9% to 48% of time is observed at level 3 of HAAR. Keywords: Background Subtraction, Illumination Variation, Multi-Level HAAR, Phase as a Feature