Image processing Benchmarks

For this benchmark the following most widely used image processing libraries were considered.

- imagemagick [http://www.imagemagick.org/script/index.php]
- graphicsmagick [http://www.graphicsmagick.org/]
- epeg [https://github.com/mattes/epeg]
- opencv [http://opencv.org/]
- vips

Test environment:
Memory: 5.8 GB
Processor: Intel Xeon CPU W3530 @ 2.80Ghz x 4 Core
OS: Ubuntu 13.04 / 64 bit
Graphics: Gallium 0.4 on AMD Redwood

Original Image - 350KB - 3168x3168 pixels | Resized to 640x480
imagemagick x 3.69 ops/sec ±2.27% (23 runs sampled)
gm x 5.03 ops/sec ±0.68% (29 runs sampled)
opencv x 19.18 ops/sec ±1.27% (49 runs sampled)
epeg x 35.49 ops/sec ±1.16% (60 runs sampled)
vips x 40.62 ops/sec ±5.01% (69 runs sampled)

Original Image - 1 MB - 3000x2000 | Resized to 640x480
imagemagick x 4.97 ops/sec ±2.35% (29 runs sampled)
gm x 5.00 ops/sec ±0.54% (29 runs sampled)
opencv x 15.15 ops/sec ±1.36% (41 runs sampled)
epeg x 27.47 ops/sec ±0.98% (69 runs sampled)
vips x 36.26 ops/sec ±6.05% (89 runs sampled)

Original Image - 15MB - 5382x6254 pixels | Resized to 640x480
imagemagick x 0.87 ops/sec ±1.20% (9 runs sampled)
gm x 0.87 ops/sec ±0.66% (9 runs sampled)
vips x 1.74 ops/sec ±0.43% (13 runs sampled)
opencv x 1.88 ops/sec ±4.09% (9 runs sampled)
epeg x 3.87 ops/sec ±0.78% (14 runs sampled)

From the above results, VIPS seems to be the fastest among all followed by epeg and opencv. But one thing to consider is the features provided vs performance. Libraries such as VIPS and EPEG are more optimized towards image resizing and image cropping while opencv, graphicsmagick and imagemagick provides a slew of image processing and analysis features.

Code snippet for benchmarking: https://gist.github.com/karthik20522/7605083