computer vision libraries

A number of libraries have appeared over the years to facilitate computer vision research, including the following:

1. Matlab. Although designed as a generic platform for matrix analysis, Matlab is popular with computer vision researchers because it is extremely easy to use and is an excellent platform for prototyping quick ideas. Nevertheless it is extremely computationally inefficient; its visualization capabilities are not tailored for image sequences; and it is not suited for large projects due to the lack of advanced software features.
2. OpenCV. This extensive library from Intel contains scores of useful computer vision functions and is probably the most popular library to date.  It runs on Windows or Linux. Unfortunately, because the code is primarily written in C using flexible structs, the user is left with the burden of mundane low-level tasks such as memory management and type safety. Although the library is open-source, it is tightly integrated with the IPL and IPP libraries described below, which are not open-source.
3. IPL. This library contained an extensive collection of image processing functions (but no computer vision routines), all hand-optimized by Intel programmers for various Pentium processors using MMX assembly language. Despite being free (no cost), this library was not open-source, and it is no longer available.
4. IPP. As the successor to the Image Processing Library (IPL) and the Signal Processing Library (SPL), this library contains a large number of functions for image processing, signal processing, and small matrix analysis, along with a few computer vision routines, all hand-optimized for Pentium processors using MMX, SSE, and SSE2 assembly language. The library is written completely in C, leaving memory management to the user.  The library is neither open-source nor free (no cost).
5. vxl. Aiming to be for computer vision what OpenGL is for graphics, this extensive open-source library (including numerics and display as well as image processing and some computer vision) works on Windows or Linux. The extensive use of templates makes for somewhat awkward syntax, there are no SIMD operations for efficient low-level processing,
6. ImLib3D. This is a much smaller library written for 3D medical imaging on Linux. It has a clean syntax, uses templates and iterators, and interfaces with the shell for non-compiled use. It is released under the GNU GPL.
7. vigra. This small library, written as part of a Ph.D. thesis, explores the application of advanced object-oriented and generic programming techniques such as templates, iterators, functors, and data accessors to computer vision. These techniques make the code very difficult for an outsider to read or use, and the license is not GPL-compatible.
8. XVision.
9. vista.
10. VisLib.
11. DARPA IUE.
12. Khoros
13. VisionLab (Netherlands)
14. Diamond3D (MERL)
15. Microsoft Vision SDK
16. LTI-Lib
17. CMVision
18. BV-Tool (split and merge)
19. CImg (cool image)
20. Imalab (Augustin Lux, Machine Vision and Applications 2004)
21. CIMPL Numerical Performance Library (Baris Sumengen) Efficient and easy to use. Version 0.1.
22. ImgSource. A commercial image processing package for reading/writing images, displaying them on the screen, and manipulating them for human viewing.
23. CVIPtools
24. ITK
25. Etc. (ImageLib, VTK, ...)