The document discusses regional descriptors in digital image processing, which categorize regions based on internal and external characteristics. Key properties such as area, perimeter, shape factor, and topology features are emphasized for modeling shapes and reflectivity properties. Additionally, it introduces concepts like Euler number and connected components to describe the topology of a region.

1. NADAR SARASWATHI
COLLEGE OF ARTS AND
SCIENCE
DIGITAL IMAGE PROCESSING
C.Murugeswari
II M.Sc Computer Science

2. REGIONAL DESCRIPTORS
Boundary descriptors use external
representations to model the shape
characteristics of regions.
Regional descriptors use internal
representations to model the internal content
of regions.
Example:
shape properties(both internal and
external)
fourier descriptors(external)

3. Regional descriptors are a type of region
description that includes area, perimeter,
, and mean value. Generally, an external
representation is chosen when a primary
focus is on shape characteristics. An
internal representation is selected when
a primary focus is on reflectivity
properties, such as color or texture.

4. Perimeter - length of region's boundary
Area - number of pixels contained within
its boundary
Shape factor - Perimeter2/Area
Range - the difference between the
largest and the smallest pixel values in a
region
 Median - median of pixels' intensity
values within the region.

7. TOPOLOGY FEATURE:
 topology - the study of properties of a figure that
are unaffected by any deformation except tearing
or folding.
 topological features give a global description of a
region examples:
 number of holes
 number of connected components
 number of object edges
 number of faces
 number of vertices
 Euler number (the difference between the number
of connected components and number of holes)

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