Information Technology

Learning OpenCV

---

The library is written in C and C++ and runs under Linux, Windows and Mac OS X. Th ere is active development on interfaces for Python, Ruby, Matlab, and other languages.
OpenCV was designed for computational efficiency and with a strong focus on real- time applications. OpenCV is written in optimized C and can take advantage of multicore processors. If you desire further automatic optimization on Intel architectures [Intel], you can buy Intel’s Integrated Performance Primitives (IPP) libraries [IPP], which consist of low-level optimized routines in many different algorithmic areas. OpenCV automatically uses the appropriate IPP library at runtime if that library is installed.
One of OpenCV’s goals is to provide a simple-to-use computer vision infrastructure that helps people build fairly sophisticated vision applications quickly. Th e OpenCV library contains over 500 functions that span many areas in vision, including factory product inspection, medical imaging, security, user interface, camera calibration, stereo vision, and robotics. Because computer vision and machine learning oft en go hand-in- hand, OpenCV also contains a full, general-purpose Machine Learning Library (MLL). Th is sublibrary is focused on statistical pattern recognition and clustering. Th e MLL is highly useful for the vision tasks that are at the core of OpenCV’s mission, but it is general enough to be used for any machine learning problem.

---

Availability

No copy data

Detail Information

Series Title

-

Call Number

-

Publisher

: ., 2008

Collation

1-577

Language

English

ISBN/ISSN

978-0-596-51613-0

Classification

NONE

Content Type

-

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Learning OpenCV

Specific Detail Info

-

Statement of Responsibility

-

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment