QR Code Patterns Localization based on Hu Invariant Moments
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 9
Abstract
The widespread utilization of QR code and its coincidence with the swift growth of e-commerce transactions have imposed the computer vision researchers to continuously devise a variety of QR code recognition algorithms. The latter performances are generally limited due to two main factors. Firstly, most of them are computationally expensive because of the implemented feature descriptor complexities. Secondly, the evoked algorithms are often sensitive to pattern geometric deformations. In this paper a robust approach is proposed, in which the architecture is based on three distinct treatments among others: 1) An image quality assessment stage which evaluates the quality of the captured image in consideration that the presence of blur decreases significantly the recognition accuracy. 2) This stage is followed by an image segmentation based on an achromatic filter through which only the regions of interest are highlighted and consequently the execution time is reduced. 3) Finally, the Hu invariant moments technique is used as feature descriptor permitting removing false positives. This technique is implemented to filter out the set of extracted candidate QR code patterns, which have been roughly extracted by a scanning process. The Hu moments descriptor is able to recognize patterns independently of the geometric transformations they undergo. The experiments show that the incorporation of the aforementioned three stages enhances significantly the recognition accuracy along with a notable diminution of processing time. This makes the proposed approach adapted to embedded systems and devices with limited performances.
Authors and Affiliations
Hicham Tribak, Youssef Zaz
Keywords
Related Articles
- EP ID EP260734
- DOI 10.14569/IJACSA.2017.080924
- Views 108
- Downloads 0
Skew correction for Chinese character using Hough transform
Chinese Handwritten character recognition is an emerging field in Computer Vision and Pattern Recognition. Documents acquired through Scanner, Mobile or Camera devices are often prone to Skew and Correction of skew...
Comparative Analysis of K-Means and Fuzzy C-Means Algorithms
In the arena of software, data mining technology has been considered as useful means for identifying patterns and trends of large volume of data. This approach is basically used to extract the unknown pattern from the la...
Hardware Segmentation on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using Xilinx System Generator
Image segmentation is considered the most critical step in image processing and helps to analyze, infer and make decisions especially in the medical field. Analyzing digital microscope images for earlier acute lymphoblas...
Secure Medical Internet of Things Framework based on Parkerian Hexad Model
Medical Internet of Things (MIoT) applications enhance medical services by collecting data using devices connected to the IoT. The collected data, which may include personal data and location, is transmitted to mobile de...
Video Streaming Analytics for Traffic Monitoring Systems
It is considered a difficult task to have check on traffic during rush hours. Traditional applications are man-ual, costly, time consuming, and the human factors involved. Large scale data is being generated from differe...