SHARP is a parallel algorithm for shape recognition designed by C. P. Ravikumar and Rajender Sethi.
This repository contains its implementation in C++ exploiting OpenMP parallel programming model. It also leverages on OpenCV to efficiently handle images.
The following results have been collected on a Macbook Pro Mid-2012 shipping a Intel(R) Core(TM) i7-3615QM CPU @ 2.30GHz.
SHARP scalability tests have been run with a maximum of 8 threads (max number of logical threads on the machine) in a live system.
| Run time [ms] with # of threads: | 1 | 2 | 4 | 8 |
|---|---|---|---|---|
| pentagon_35_degrees.jpg | 22.90 | 12.70 | 12.40 | 8.20 |
| tr_oval.jpg | 42.20 | 23.30 | 16.80 | 14.40 |
| duck_scaled_15_degrees.jpg | 18.70 | 11.70 | 6.80 | 13.50 |
| duck_scaled_50_degrees.jpg | 18.80 | 12.60 | 5.90 | 13.60 |
| oval_45_degrees.jpg | 28.00 | 15.20 | 10.90 | 9.80 |
| oval_90_degrees.jpg | 24.20 | 12.80 | 10.40 | 8.20 |
| stewie_135_degrees.jpg | 49.60 | 27.70 | 27.50 | 16.20 |
| hexagon_135_degrees.jpg | 23.10 | 13.90 | 11.60 | 10.70 |
