CRISP: Real-Time Interactive Signal Processing Library (v0.9.2)

What is crisp?

crisp is a library implementing most image-processing needs from scratch. This includes:

• Spatial Filtering
• Morphological Transform
• Fourier Transform & Spectral Filtering
• Edge Detection
• Segmentation & Clustering
• Feature Extraction
• Boundary and Texture Descriptors
• Neural Networks (fully connected and convolutional)
• GPU-side hardware acceleration
• Bayes Classification
• SIFT & Key Point Classification
• Color Representations
• Noise Modelling
• Histogram Equalization & Specialization
• Wavelet Transforms
• Bitplane Decomposition & Watermarking

Why crisp?

crisp is visual
Render anything! Really, anything?
It's called visual computing, after all. Here's a non-exhaustive list of things you can draw on your screen or save to an image at any time:

• crisp::Image of any type
• crisp::FourierTransform
• crisp::FrequencyDomainFilter
• crisp::Kernel
• crisp::StructuringElement
• crisp::Histogram
• Eigen::Matrix<T, /*...*/>
• crisp::ConvolutionalNeuralNetwork
• and more!

This makes debugging, filter design or just understanding/explaining your own algorithms much easier and more intuitive.

crisp is fast

• for best performance, crisp::Texture lives in VRAM and is operated upon by the GPU
• GPU-side computation makes large-scale real-time processing possible on mid-end machines
• Example: crisp::HardwareAcceleratedMatrix offers excellent runtime even for very large matrices
  
  
  

crisp is flexible

• crisp::Image lives in RAM
• extremely intuitive, pixels are stored in a 2D array and each can be accesses freely
• runs on tiny embedded system with 1 core and no graphics card

crisp is well documented

• full tutorials are available for all features
• examples with images are provided whenever possible
• in-line documentation for IDE support
• user-facing code is polished to a mirror sheen
• language is kept simple, aimed at people without a math degree

crisp is generic

• filter, segment, cluster in any number of dimensions, any image value type
• convert any image type to any other image type
• convert any color representation to any other color representation
• compare/combine vectors with vectors, vectors with scalars, vectors with matrices all using the same operators

crisp is portable

• supports Mac, Linux and Windows
• runs on tiny 1-cpu machines like embedded systems
• also makes full use of strong machines' multiple processors, hardware-acceleration

Installation

Dependencies

• C++20 or newer
• cmake
• gcc10 or newer
  • libgcc-10-dev
• OpenGL 3.3 ES or newer
  • libopengl-dev
• Eigen
  • provided as submodule
  • libeigen3-dev
• SFML
  • libsfml-system2.5
  • libsfml-window2.5
  • libsfml-graphics2.5
• fftw3
  • libfftw3-bin
  • libfftw3-single3
  • libfftw3-double3
  • libfftw3-long3
  • libfftw3-quad3
• lua5.3
  • lua5.3 package
• Video I/O
  • libopencv-core4.5
  • libopencv-videoio4.5

Installation

crisp is header only, to add it to your project, simply use:

git clone https://github.com/Clemapfel/crisp.git

or if you already have a project folder:

git submodule add https://github.com/Clemapfel/crisp.git

Add the corresponding include path to your cmake script and link against crisp like so:

include_directories("/path/to/.../crisp/include/")
add_executable(MY_EXECUTABLE path/to/my/main.cpp)
target_link_libraries(MY_EXECUTABLE crisp)

Be sure to compile with gcc10 or newer, as many needed C++20 features are not supported in older versions. If linker errors appear, make sure all dependencies and packages listed above are installed on a system level.

Tutorials

Consider reading the tutorials in order, this will teach important principles of crisp (and image processing in general) step-by-step:

1. System
2. Vector
3. Images
4. Color
5. Noise (optional)
6. Spatial Domain Filters
7. Morphological Transform
8. Frequency Domain Filters
9. Segmentation
10. Feature Extraction
11. Deep Learning
12. Hardware Acceleration
13. Video

Documentation

Documentation is stored as interactive markdown files, right here on github. An index for easy navigation can be found here or in /crisp/docs/.