Importance of image tresholding
Answers
Thresholding means converting image into binary format. It is important for image processing. Because, some time people need separation of dark and light region. Thresholding image can separate dark and light side of the colorful image. Another reason is, you can convert binary image in any format using that. To make the image binary, you have to go to adjustment tool and select “Threshold”. That’s an easy way to do this.
Importance of thresholding: The digitalization of root
sample is a performed by normal desktop scanner or by scanner with additional TPU unit allowing the illumination from
Bouma et al. (2000) refers that a proper scanning protocol is much more important than the software used, and
that the protocol should thus always be listed; however
the authors also stress the importance of proper threshold
selection, suggesting that higher threshold values can cause
more appropriate length estimation though causing incorrect diameter measurements. Zobel (2008) mentioned that
threshold is the key factor when determining the size of an
object in grey levelled images, concluding that none of existing software is capable of adequate analysis of different
type of digital images representing the fine roots. Smit et al.
(1994) developed automated 3d measurement technique of
fine roots. He suggested using histogram based segmentation
of roots from background. Richner et al. (2000) demonstrated for the segmentation of washed root samples, the grey-
-level thresholding technique is used most frequently. When
using thresholding, the most critical step is to define (to set)
the grey-level threshold. In a few cases, two threshold grey-
-levels are used instead of just one (Smit et al. 1994; Kaspar
& Ewing 1997). The two threshold levels define the upper
and the lower limit of the range of grey-levels belonging to the
roots. When decreasing the threshold grey-level to resolve
the thinnest roots in a sample, more background pixels along
the root boundaries are classified as object pixels and, thus,
the contours of thicker roots will blur and expand. In addition, a great deal of noise may occur in the image as a result of
a too low grey-level threshold. Staining roots may eliminate
some of the problems involved in thresholding, though not
completely. In summary, simple grey-level thresholding is
appropriate only if there is a good contrast between roots and
background and a uniform lighting of the whole scanning
area. Because these requirements are most often not met, it
is difficult to visually determine the optimal threshold value
(Tollner et al. 1994).