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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.
Mimas Toolkit project 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.
Mimas was originally conceived as a platform for real-time machine vision research. Its aim was and still is to reduce the turnaround time of new research into the application workspace. It is written in C++ and is released in source code form subject to the GNU Lesser General Public License (LGPL).
Mimas has been used to build a number of vision systems including for two European Union sponsored projects, namely MINIMAN (completed in 2002) and MiCRoN (expected to complete in the 3rd quarter of 2005). Mimas is also being used to build a number of customised vision solutions for academia and industry. As such, if you do require a vision-based solution then please contact the authors of this software.
Main features:
- generic image class (greylevel and colour)
- low level image processing
- frequency domain processing
- variety of recognition methods
- variety of tracking methods
- active contours
- comprehensive matrix library
- variety of statistical operations
- associative neural network
- multi-layer perceptrons ANN
- image capture
- various example interfaces
Mimas is designed to be platform independent from the ground-up. Hence a user interface is not built-in. Rather Mimas acts as the engine of a vision system. Since it is written in C++, we recommend that you use the GPL-ed version of the cross-platform Qt toolkit or the Mozilla XP toolkit for building user interfaces.

PHP Web Toolkit provides a rapid development toolkit for multi-layered Web applications written in PHP 5.

The PHP Web Toolkit enables the rapid development of multi-layered Web applications and is designed to be easy to use, extensible, reliable, reusable, scalable, and secure. It integrates with ADOdb, FCKeditor, kses, Libmcrypt, Libmhash, and Smarty.

Raptor RDF Parser Toolkit is a free software and Open Source C library that provides a set of parsers and serializers that generate Resource Description Framework (RDF) triples by parsing syntaxes or serialize the triples into a syntax.

The supported parsing syntaxes are RDF/XML, N-Triples, Turtle, RSS tag soup including Atom 1.0 and 0.3, GRDDL for XHTML and XML. The serializing syntaxes are RDF/XML (regular, and abbreviated), N-Triples, RSS 1.0, Atom 1.0 and Adobe XMP.

Raptor was designed to work closely with the Redland RDF library (RDF Parser Toolkit for Redland) but is entirely separate. It is a portable library that works across many POSIX systems (Unix, GNU/Linux, BSDs, OSX, cygwin, win32). Raptor has no memory leaks and is fast.

The Digital Invisible Ink Toolkit is a Java steganography tool that can hide any sort of file inside a digital image (regarding that the message will fit, and the image is 24 bit colour). Digital Invisible Ink Toolkit will work on Linux and Max OS, even on Windows because it is written in Java and thus platform independent.

There are four highly customisable algorithms in the tool, as well as an open-source implementation of RS Analysis (an extremely good steganalysis method). The tool has the additional advantage of being able to simulate hiding - so you can get an accurate map of where the information is hidden.

The compiled version can be run by simply double clicking the .jar file, or by running at a command line with the following options (you will need to run at the command line if you are using big pictures, such as those greater than 500x500 pixels or it will run out of memory):

java -jar -Xmx512m diit_1-1.jar

Where -Xmx512m tells the virtual machine to use 512MB of physical RAM (at most) - please change to suit your own machine specifications.

libcontain library provides a large and growing number of fast and thread-safe containter objects written in C and C++.
The libcontain library now provides the following container types:
- a series of hash tables libcontain includes the hash table implementation from GNU glib and a hash implementation in C++ it inherited from the libhash library it originates from. This latter has been rendered thread-safe in the 0.2 release and implements a linear hashing algorithm. A single hash table implementation that will replace them both is on the drawing boards and is intended to be thread-safe and non-blocking.
- an array (vector) implementation
libcontain currently includes a non-blocking array implementation. However, this implementation presents a race-condition in concurrent calls to any of its writing functions if the array is in the process of being resized. There is currently no known non-blocking way to solve this race condition. Help is welcome in this area.
- a binomial tree
The binomial tree provided by libcontain does not provide any algorithmic logic in its implementation: it is a generic container that can be used as the basis for other container implementations, such as a heap or a map (as a matter of fact, the heap and the map are both based on this binomial tree)
- a heap
libcontain provides an automatically sorting heap implementation that (obviously) uses a heap sort to sort the elements it contains. Unfortunately, the heap implementation is not non-blocking (although bases on a non-blocking binomial tree implementation). It contains four levels of locks: a reader count and a write lock at the level of the nodes, and a reader count and a write lock at the level of the container. The locks are posed on the container for as short a time as possible so at to prevent the progress of the algorithm to block too long. If anyone knows of a non-blocking heap algorithm, input is more than welcome.
- a list
libcontain provides a non-blocking list implementation based on an algorithm by M.M. Micheal (also the inventor of Safe Memory Reclamation on which libmemory is based).
a map
The map implementation included in libcontain is based on the binomial tree implementation. Unlike some implementations based on binary trees, this implementation stores values in each node of the tree (not just the leaf nodes) and therefore allows a more memory-efficient way to store information than hashes and other map implementations. Also, the map implementation does not use a "less" function but uses a three-way comparison to compare keys (much like the helper function used by qsort). The implementation is almost (but not quite) non-blocking: for most intents and purposes, there are no real locks: read and write operations may be re-directed along a branch of the binomial tree if a node that they traverse is being deleted, but will not block for that. However, a remove operation will wait for another remove operation to finish if it traverses a node being removed.
- a queue
a non-blocking queue implementation is provided
- a stack
a non-blocking stack implementation is also provided
In future versions, the hash implementation will be replaced by a non-blocking one and the remaining problems with the existing containers will (hopefully) be solved. Help is also needed to write the architecture-dependant code for non-IA32 platforms such as Sparc.
Enhancements:
- The 0.2 release introduces number of important new features including a heap and a map, both based on a lock-free binomial tree. It also includes the required memory management to make the containters impervious to the ABA problem and thus truly thread-safe.

Medical Imaging Interaction Toolkit (MITK) is currently under active development, and aims at supporting the development of leading-edge medical imaging software with a high degree of interaction. It combines vtk, itk and the pic-based-libraries of the Div.
Main features:
- multiple, consistent views on the same data. For example, when you have three orthogonal 2D-views and a 3D view and data consisting of a green surface, the surface will be visible and green in all views (as contour lines in 2D, as a surface in 3D), and when you move the surface, it will move in all views. When you try to realize this with basic vtk, you will need to coordinate the position/orientation/color/... of all the views somewhere in your program - exactly this can mitk do for you.
- interactions that create and/or modify data (not only actors as in basic vtk)
- complex interactions with multiple states, e.g., for interaction with active contours
- undo/redo of interactions
- organization of data objects in a tree at run-time, e.g., to represent logical dependencies (e.g., a heart cavity is a part of the heart) or to control the rendering process
- additional properties of arbitrary type can be assigned to data objects contained in the data tree
- visualization and interaction with 3D+t data (basic vtk can handle only 3D data and itk is not for visualization and interaction)
- although mitk is mainly a toolkit and not an application, it offers some support on the application-level, e.g, for structured combination of modules (so-called functionalities), e.g., for combining and switching between one functionality for segmentation and another for registration.
Enhancements:
- New functionalities: IsoSurface, ViewInitialization and Measurement.
- Support for ITK 2.4-2.8, VTK 4.4 and 5.0.
- Lots of bugfixes and improvements, e.g. interaction for rotatable slices.

The CentralNic Toolkit is CentralNics system for instantaneous Registry-Registrar Communications. Registrars can use this system to register and modify domain names in real time, with no delays for human intervention or e-mail processing.
CentralNic Toolkit also provides advanced and efficient methods for searching for and querying domain names and whois records, and retrieving account information.
All the software developed for the Toolkit system is Open Source, and is developed in a participatory manner, relying on cooperation with our user base. Users of the software are encouraged to submit bugs, suggestions, feature requests and patches.
Enhancements:
- This release adds support for the new account management functions that allow automation of payment batches.