Van de Loosdrecht Machine Vision BV
Company was founded in 2001Core business Machine Vision (Image Processing)
- Development of the image processing system VisionLab
- Image processing algorithms
- Neural networks
- Genetic algorithms
- Pattern matching
- Algorithms written in ANSI C++
- OpenMP
- OpenCL
- Portable software, running under Windows, Linux and Android on x86, x64, ARM and PowerPC
News
VisionLab interfaces with all major Deep Learning frameworks that have a Python interface
Deep Learning
New Hyper-Spectral Imaging operators are under development Hyper-Spectral Imaging
New Open Online Course How to build a car licence plate recogniser using a regression test framework in C#
New enhanched version of VisionLab GUI,screenshot
Inauguration speech Jaap van de Loosdrecht, Professor Computer Vision, NHL-Stenden University of Applied Sciences
Download inaguration speech (Dutch)
VisionLab is used in developing the new Twirre architecture for autonomous UAVs using interchangeable commodity components. The Twirre architecture was presented at the The Unmanned System Expo and International Micro Air Vehicle Conference.
Thesis Accelerating sequential machine vision algorithms using commodity parallel hardware available for download.
VisionLab is used in a Feasibility Study with XIMEA CURRERA-G smart camera with enhanced GPU.
New version of VisionLab V3.46 (September 2018) available in download section:
New Hyper-Spectral Imaging operators are under development Hyper-Spectral Imaging
New Open Online Course How to build a car licence plate recogniser using a regression test framework in C#
New enhanched version of VisionLab GUI,screenshot
Inauguration speech Jaap van de Loosdrecht, Professor Computer Vision, NHL-Stenden University of Applied Sciences
Download inaguration speech (Dutch)
VisionLab is used in developing the new Twirre architecture for autonomous UAVs using interchangeable commodity components. The Twirre architecture was presented at the The Unmanned System Expo and International Micro Air Vehicle Conference.
Thesis Accelerating sequential machine vision algorithms using commodity parallel hardware available for download.
VisionLab is used in a Feasibility Study with XIMEA CURRERA-G smart camera with enhanced GPU.
New version of VisionLab V3.46 (September 2018) available in download section:
- Multi Core Processing with automatic operator parallelization for more than 170 operators, available for all supported processors
- Scripts and programs will run faster without modification
- Windows 10 x64 version
- Linux x64 and ARM version
- Raspberry PI (2) and ODRIOD C1/XU4 versions
- Android version
- HTML help, see help file
- XIMEA xiAPI camera interface
- Basler Pylon camera interface
- IDS uEye camera interface
- Tethering with Nikon and Canon DSLR cameras
- Toolbox for using OpenCL kernels from scripts and C++
- SWIG interface, example of using VisionLab directly from C#
- SDK for Visual Studio 2017 and GNU C++ compiler
- See change history for all changes
Thesis
Accelerating sequential machine vision algorithms using commodity parallel hardware
- Research project in collaboration with the Limerick Institute of Technology in Ireland and the NHL University in the Netherlands
- This project focus on both multi-core CPUs and GPUs
- Tools used are C++, OpenMP and OpenCL
- Download thesis
- Course material about acceleration vision algorithms using OpenMP and OpenCL