IPA::Morphology - morphological operators
Quote from http://www.dai.ed.ac.uk/HIPR2/morops.htm:
Morphological operators often take a binary image and a structuring element as input and combine them using a set operator (intersection, union, inclusion, complement). They process objects in the input image based on characteristics of its shape, which are encoded in the structuring element.
Usually, the structuring element is sized 3x3 and has its origin at the center pixel. It is shifted over the image and at each pixel of the image its elements are compared with the set of the underlying pixels. If the two sets of elements match the condition defined by the set operator (e.g. if the set of pixels in the structuring element is a subset of the underlying image pixels), the pixel underneath the origin of the structuring element is set to a pre-defined value (0 or 1 for binary images). A morphological operator is therefore defined by its structuring element and the applied set operator.
Morphological operators can also be applied to gray-level images, e.g. to reduce noise or to brighten the image.
Applies 512-byte lookup
LUT string ( look-up table ) to image and returns the convolution result ( hit-and-miss transform).
Each byte of lookup
is a set of bits,
each corresponding to the 3x3 kernel index:
|4 3 2| |5 0 1| |6 7 8|
Thus, for example, the X-shape would be represented by offset 2**0 + 2**2 + 2**4 + 2**6 + 2**8 = 341 . The byte value, corresponding to the offset in lookup
string is stored in the output image.
IPA::Morphology
defines several basic LUT transforms, which can be invoked by the following code:
IPA::Morphological::bw_METHOD( $image);
or its alternative
IPA::Morphology::BWTransform( $image, lookup => $IPA::Morphology::transform_luts{METHOD}->());
Where METHOD is one of the following string constants:
Morphological dilation
Morphological erosion
Remove isolated pixels
Convert binary image to grayscale by applying the mean filter
Inversion operator
Removes 1-connected end points
Removes node points that connect 3 or more lines
Supported types: Byte
Performs morphological dilation operation on IMAGE and returns the result. neighborhood
determines whether the algorithm assumes 4- or 8- pixel connectivity.
Supported types: Byte, Short, Long, Float, Double
Performs morphological erosion operation on IMAGE and returns the result. neighborhood
determines whether the algorithm assumes 4- or 8- pixel connectivity.
Supported types: Byte, Short, Long, Float, Double
Performs morphological opening operation on IMAGE and returns the result. neighborhood
determines whether the algorithm assumes 4- or 8- pixel connectivity.
Supported types: Byte, Short, Long, Float, Double
Performs morphological closing operation on IMAGE and returns the result. neighborhood
determines whether the algorithm assumes 4- or 8- pixel connectivity.
Supported types: Byte, Short, Long, Float, Double
Returns the result or the morphological gradient operator on IMAGE. neighborhood
determines whether the algorithm assumes 4- or 8- pixel connectivity.
Supported types: Byte, Short, Long, Float, Double
Performs the algebraic difference between IMAGE1 and IMAGE2. Although this is not a morphological operator, it is often used is conjunction with ones. If the boolean flag inPlace
is set, IMAGE1 contains the result.
Supported types: Byte, Short, Long, Float, Double
Applies the watershed segmentation to IMAGE with given neighborhood
.
Supported types: Byte
Performs morphological reconstruction of IMAGE1 under the mask IMAGE2. Images can be two intensity images or two binary images with the same size. The returned image, is an intensity or binary image, respectively.
If boolean inPlace
flag is set, IMAGE2 contains the result.
neighborhood
determines whether the algorithm assumes 4- or 8- pixel connectivity.
Supported types: Byte, Short, Long, Float, Double
Applies the skeletonization algorithm, returning image with binary object maximal euclidian distance points set.
Supported types: Byte