Abstract: Noise contamination in a magnetic resonance (MR)
image could occur during acquisition, storage, and transmission in
which effective filtering is required to avoid repeating the MR
procedure. In this paper, an iterative asymmetrical triangle fuzzy
filter with moving average center (ATMAVi filter) is used to reduce
different levels of salt and pepper noise in a brain MR image. Besides
visual inspection on filtered images, the mean squared error (MSE) is
used as an objective measurement. When compared with the median
filter, simulation results indicate that the ATMAVi filter is effective
especially for filtering a higher level noise (such as noise density =
0.45) using a smaller window size (such as 3x3) when operated
iteratively or using a larger window size (such as 5x5) when operated
non-iteratively.
Abstract: In this paper, an extended study is performed on the
effect of different factors on the quality of vector data based on a
previous study. In the noise factor, one kind of noise that appears in
document images namely Gaussian noise is studied while the previous
study involved only salt-and-pepper noise. High and low levels of
noise are studied. For the noise cleaning methods, algorithms that were
not covered in the previous study are used namely Median filters and
its variants. For the vectorization factor, one of the best available
commercial raster to vector software namely VPstudio is used to
convert raster images into vector format. The performance of line
detection will be judged based on objective performance evaluation
method. The output of the performance evaluation is then analyzed
statistically to highlight the factors that affect vector quality.