The process of pattern recognition is divided into several sub-steps where ultimately patterns on unknown data samples are expected to be detected and automatically labeled. Classiffers are most commonly used for this and are being trained on known test data samples. Many existing software applications provide tools for selected tasks in pattern recognition but not for all steps in the training phase. Therefore in this work a framework was developed which implements common tasks of image classiffcation systems as individual components. It is plugin aware, easily extensible and provides a graphical user interface.