SIP provides image processing, pattern recognition, and computer vision routines for SciLab, a Matlab-like matrix-oriented programming environment. SIP is able to read/write images in almost 90 major formats, including JPEG, PNG, BMP, GIF, FITS, and TIFF. It includes routines for filtering, segmentation, edge detection, morphology, curvature, fractal dimension, distance transforms, multiscale skeletons, and more.
libagf is a fast, innovative implementation of adaptive or variable-bandwidth kernel-based estimators for statistical classification, PDF estimation, and interpolation/non-linear regression. It is written in C++ and includes simple, command line executables as well as easy-to-use libraries.
The LTI-Lib is an object oriented library with algorithms and data structures frequently used in image processing and computer vision. It was developed at the RWTH-Aachen University as a part of many research projects on computer vision dealing with robotics, object recognition, sign language, and gesture recognition. It provides an object oriented C++ library that includes fast algorithms, which can be used in real applications.
CellWriter is a grid-entry natural handwriting input panel. As you write characters into the cells, your writing is instantly recognized at the character level. When you press 'Enter' on the panel, the input you entered is sent to the currently focused application as if typed on the keyboard. Writer-dependent, CellWriter learns your handwriting for reliable recognition. Correcting preprocessor algorithms account for digitizer noise, differing stroke order, direction, and number of strokes. Unicode support enables you to write in any language.
VXL is a set of portable C++ libraries designed for computer vision research and implementation. Numerics, imaging, and geometry are provided by stand-alone core libraries, with easy to use APIs and sophisticated processing algorithms. Other libraries provide stereo, video, structure from motion, probability modeling, GUI design, classification, robust estimation, feature tracking, topology, 3d imaging, and much more. It is written and used by an international team from academia and industry.
SIOX4Java (Simple Interactive Object Extraction) is a Java SDK that provides a generic segmentation engine for extracting the foreground from still images with little user interaction. The underlying method (which has also been integrated into GIMP) is noise and motion blur robust and can easily be adapted for the segmentation of objects in videos. The SDK also contains an experimental feature called the "Detail Refinement Brush", which enables the removal of spill colors and manual refinement of highly detailed textures.
The Pattern Recognition Application Programmer's Interface aims to be a fully-featured, easy-to-use general C++ framework for various pattern recognition tasks, especially image analysis. It features support for many image formats, well-known image analysis methods, classification and feature analysis tools, XML serialization, etc.
Mimas Toolkit is a C++ computer vision toolkit. It is easy to use and includes tools for edge detection, corner detection, various filters, optic flow, tracking, blob analysis, Web cam tools for real-time applications, and much more. It also includes many implementations of traditional algorithms such as Canny. It was developed for GNU/Linux but as the GUI is largely separate, porting to other platforms should be straightforward.
The OMCSNet-WordNet project aims to improve the quality of the OMCSNet dataset by using automated processes to map WordNet synonym sets to OMCSNet concepts and import additional semantic linkage data from WordNet. It is based on OMCSNet 1.2, a semantic network and inference toolkit written in Python/Java. OMCSNet currently contains over 280,000 separate pieces of common sense information extracted from the raw OMCS dataset. This project is also based on WordNet, an online lexical reference system that in recent years has become a popular tool for AI researchers.