Determining adaptive thresholds for image segmentation for a license plate recognition system
2016
A vehicle license plate recognition (LPR) system
is useful to many applications, such as entrance admission,
security, parking control, airport and cargo, traffic and speed
control. This paper describe an adaptive threshold for image
segmentation applied to a system for Malaysian intelligent license
plate recognition (MyiLPR). Due to the different types of license
plates used, the requirements of an automatic LPR system are
rather different for each country. Upon receiving the input car
image, this system (MyiLPR) detects and segments the license
plate based on proposed adaptive threshold via image and
blob histogram, and blob agglomeration, and finally, it extracts
geometric character features and classifies them using neural
network. The use of the proposed adaptive threshold increased the
detection, segmentation and recognition rate to 99%, 94.98% and
90% correspondingly, from 95%, 78.27% and 71.08% obtained
with the fixed threshold used in the originally proposed system
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
28
References
3
Citations
NaN
KQI