Home / WPF / Getting started with real-time image processing with C#. Getting started with real-time image processing with C#. H.265 / H.264 / MJPEG). Anyway rtsp is kind of complicated. Onvif you can have a look at this article for the image acquisition. Image processing c source code free download. Convert3D Medical Image Processing Tool C3D is a command-line tool for converting 3D images between common file formats. The tool also inclu.
Digital Background. Secure data concept. Digital flow, symbolizing data protection and digital technologiesThe acquisition and processing of a video stream can be very computationally expensive. Typical image processing applications split the work across multiple threads, one acquiring the images, and another one running the actual algorithms. In MATLAB we can get multi-threading by interfacing with other languages, but there is a significant cost associated with exchanging data across the resulting language barrier.
In this blog post, we compare different approaches for getting data through MATLAB’s Java interface, and we show how to acquire high-resolution video streams in real-time and with low overhead.MotivationFor our booth at ICRA 2014, we put together a demo system in MATLAB that used stereo vision for tracking colored bean bags, and a robot arm to pick them up. We used two IP cameras that streamed video over. While developing the image processing and robot control parts worked as expected, it proved to be a challenge to acquire images from both video streams fast enough to be useful.only supports over and didn’t exist at the time.only supports USB cameras.and are limited to HTTP and too slow for real-timeSince we did not want to switch to another language, we decided to develop a small library for acquiring video streams. The project was later open sourced as. Technical BackgroundIn order to save bandwidth most IP cameras compress video before sending it over the network. Since the resulting decoding step can be computationally expensive, it is common practice to move the acquisition to a separate thread in order to reduce the load on the main processing thread.Unfortunately, doing this in MATLAB requires some workarounds due to the language’s single threaded nature, i.e., background threads need to run in another language.
Out of the box, there are two supported interfaces: for calling C/C code, and the for calling Java code.While both interfaces have strengths and weaknesses, practically all use cases can be solved using either one. For this project, we chose the Java interface in order to simplify cross-platform development and the deployment of binaries.
![Processing Processing](/uploads/1/2/5/4/125446383/620540819.jpg)
The diagram below shows an overview of the resulting system.Figure 1. System overview for a stereo vision setupStarting background threads and getting the video stream into Java was relatively straightforward. We used the library, which is a Java wrapper around and that includes pre-compiled native binaries for all major platforms.
However, passing the acquired image data from Java into MATLAB turned out to be more challenging.The Java interface automatically converts between Java and MATLAB types by following a set of. This makes it much simpler to develop for than the MEX interface, but it does cause additional overhead when calling Java functions. Most of the time this overhead is negligible. However, for certain types of data, such as large and multi-dimensional matrices, the default rules are very inefficient and can become prohibitively expensive. For example, a 1080x1920x3 MATLAB image matrix gets translated to a byte108019203 in Java, which means that there is a separate array object for every single pixel in the image.As an additional complication, MATLAB stores image data in a different memory layout than most other libraries (e.g. OpenCV’s Mat or Java’s BufferedImage).
While pixels are commonly stored in row-major order ( widthheightchannels), MATLAB stores images transposed and in column-major order ( channelswidthheight). For example, if the Red-Green-Blue pixels of a BufferedImage would be laid out as RGBRGBRGB, the same image would be laid out as RRRGGGBBB in MATLAB. Depending on the resolution this conversion can become fairly expensive.In order to process images at a frame rate of 30 fps in real-time, the total time budget of the main MATLAB thread is 33ms per cycle. Thus, the acquisition overhead imposed on the main thread needs to be sufficiently low, i.e., a low number of milliseconds, to leave enough time for the actual processing.
Data TranslationWe benchmarked five different ways to get image data from Java into MATLAB and compared their respective overhead on the main MATLAB thread. We omitted overhead incurred by background threads because it had no effect on the time budget available for image processing.The full benchmark code is available.1. Default 3D ArrayBy default MATLAB image matrices convert to byteheightwidthchannels Java arrays.