Marvin - Image Processing Framework 1.3.1
Marvin - Image Processing Framework 1.3.1 Ranking & Summary
Marvin - Image Processing Framework 1.3.1 description
Marvin - Image Processing Framework 1.3.1 is considered as a professional and useful, open source image processing framework developed in Java. The framework provides features to:
- manipulate images;
- manipulate captured video frames;
- multithreading image processing;
- integrate plug-ins with Graphical User Interface(GUI);
- analyze plug-in performance;
- extend features via plug-ins;
- unit test automation;
The image processing algorithms are implemend as a plug-in and can be plugged into other plug-ins, thirdy-party applications and the MarvinEditor - an image editing software. Currently, there are 44 plug-ins available for a wide range of different purposes.
- Plug-ins: Algorithms to manipulate images are externally implemented as plug-ins. The framework provides an interface to manipulate plug-ins.
- Video Capturing: Video capturing is provided via Java Media Framework and allows developers to work with real-time video processing. For the plug-ins, the interface to work with videos and images are the same. In the case of videos, plug-ins can store past frames to analize multiple frames.
- Multi-threading: Marvin allows the processing of multiple images at the same time or the same image processed by multiple threads. Image processing plug-ins receive an image to be processed and a mask containing what pixels must be considered.
- Performance Meter: Many image processing algorithms can be divided in few processes. An algorithm, for example, may be divided in five processes to find and segment the interest points of an image: representing the image in gray scale, border detection, binarization, Harris/Plassey application, render red points representing interest points. Each process has a different computational cost and the performance meter allows developers to analyze the performance of the entire algorithm and their processes individually, considering the number of steps and the execution spent time. Thus, it is possible a better understanding of the algorithm performance and facilitates optimizations, since is visible what algorithm processes are costly and most interesting to be optimized. Another performance meter application is to determine the complexity of an algorithm, Big-O notation, analyzing the number of steps executed for different image resolution. The image below presents the informations provided by the performance meter for the plug-in "Interest points".
- GUI API: The plug-ins can have user specified attributes that determines how it works and the Marvin framework provides features to integrate a GUI (Graphical User Interface) with these attributes. The Plug-in developer sets the relation between the plug-in attributes and the interface components, added to the plug-in window. When the component value is changed, the associated attribute value is changed automatically. The developer does not worry about handling component events or update the attributes.
- Plug-in History: In some cases to achieve some result in an image, it is necessary to use a few processes. Preparing an image for pattern recognition, for example, in some applications it is interesting to remove noise, increase contrast and emphasize edges. For these cases that multiple processes are used, MarvinPluginHistory stores all plug-ins and their configurations applied to an image. The history can be exported as an image strip containing the configuration and resulting images of each used plug-in. This feature allows an analysis of an entire process considering each step. Other application is the comparison of the same application but with different settings.
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