SUBTOPICS

Pixel Types - Pixel representations IO - Image Input and Output Edges - Edge detection and processing Segmentation - Image segmentation. Morphology - Morphological operators Misc - Misc functions and tools Converters - Image convertion functions Video - Video Sequences Filtering - Image filtering Warping - Image scaling and warping Lines - Line detection and extraction Corner Detection - Corner Detectors Tracking - 2D Feature tracking

Image and video processing

The basic image class is the template class ImageC, often templated on one of the pixel classes.

In terms of its structure and functionality, ImageC and its derivatives can be considered as 2-D arrays. If there is a difference in philosophy between ImageC and Array2dC, it is that in ImageC there is a sense of neighbourhood, and spatial extent. In particular an ImageC object contains one or more "image rectangles" (ImageRectangleC). When an image is constructed, it has one associated rectangle corresponding to the border of the image. However other rectangles can also be attached, corresponding to subimages; they can also be moved around the image. These can be useful for spatial filtering and other neighbourhood operations.

Image IO:

There is a comprehensive I/O package within RAVL, including image I/O. It can deal with a large and expanding range of file formats.

Indexing images:

• Simple C-style indexing:

  Simple image constructors [e.g. ImageC::ImageC(UIntT rows, UIntT columns) ] will use a coordinate system whose origin is the top left-hand pixel. However other coordinate systems are possible. For instance, a spatial filtering operation using a 3x3 mask will typically produce an image that is smaller than the original - the whole image border has shrunk by one pixel. The coordinate system of the new image will be such that corresponding pixels in the two images have the same coordinates. Hence the coordinates of the top left-hand pixel of the old and new images will be respectively (0,0) and (1,1). The programmer does not need to keep track of these changes though - use the image rectangle or the border member functions [ImageC::TRow(), BRow(), LCol() and RCol() ] to determine the image boundaries. It is recommended to use IndexC, Index2dC for indexing images, as these have division and modulo operators that behave sensibly for negative coordinates (unlike int).

• Using RAVL image iterators: The indexing philosophy just described can often be more compactly and speedily implemented using the array iterator mechanism. For an elementary example of its usage, look at the example in Array2dIterC.

Normal classes:

ImageRectangleC	Image Rectangle.
ImageC	Basic Image

Normal functions:

DrawFrame(Array2dC &,const DataT &,const IndexRange2dC &)	Draw a rectangle in an image.
DrawLine(Array2dC &,const DataT &,const Index2dC &,const Index2dC &)	Draw a line in an image.
DrawCross(Array2dC &,const DataT &,const Index2dC &,UIntT)	Draw a cross in an image.
DrawCircle(Array2dC &,const DataT &,const Index2dC &,IntT)	Draw a circle in an image.