A blob is defined as a region of connected pixels. Blob analysis is the
identification and examination of these regions in an computer image. The
pixels are divided in one of two categories: the foreground (typically
pixels with a non-zero value or white) or the background (pixels with a zero
value or white).
In typical applications that use blob analysis, the blob features usually
calculated are area and perimeter, diameter, shape, and location.
The versatility of blob analysis tools makes them suitable for a wide
variety of applications:
- inspection of food for foreign matter
- size measurement
- identification by shape, position or size
Since a blob is a region of touching pixels, analysis tools typically
consider touching foreground pixels to be part of the same blob.
Consequently, what is easily identifiable by the human eye as several
distinct but touching blobs may be interpreted by software as a single blob.
Furthermore, any part of a blob that is in the background pixel state
because of lighting or reflection is considered as background during
Blob4 is a Blob3 with integrated
A simpler blob tool is included in the Basic
The figure below shows a
blob that is a continuous area with the same shading limited by a contour, and
possibly a number of internal holes.
Hole area 1 = H1
Hole area 2 = H2
Blob area = A
Contour area = A+H
on a set of filtering criteria, the Blob4 tool finds one or more (currently
up to 32) blobs (areas
within a contour) within the region of interest (ROI).
The following results are calculated:
- blob count
- total blob area
- Properties of the largest blob
- Individual properties for the
set of qualified blobs
Shape - Size Classification
The image shows the power of feature classification - the pills are
easily divided into two classes - pill and half pill.
tool delivers an output (child) reference coordinate system that is the
incoming reference system translated to the center of gravity of, and
rotated to the major axis of, the largest
(or first, if sorted) blob found.