Incomplete Barcode Reading Mechanism with Remote Database Access

Fang, Jyh Perng; Chang, Yang-Lang; Chu, Wei-Chieh; Chen, Kuo-Wei

doi:10.1007/978-3-642-25781-0_103

Cited by 4 publications

(2 citation statements)

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“…For nearly all the treatments there was either no difference at all or the observed differences were so highly significant that the p-values are practically equal to 0 (Table 3). PNB had the best detection at the two speeds of all the dirt treatments which could be due to its slightly wider bar arrangement and size compared to that of the PB [9,10,[17][18][19]34,37] .…”

Section: Robustness Of the Automated Image-based Barcode Detection Symentioning

confidence: 99%

“…Therefore, one has to get close to the barcodes with the scanner before the sensor can generate a reading. Also dirty, damaged, faded and multiple barcodes cannot be read or are difficult to read, and there is also the risk of losing some barcodes in the production process [9,10,[15][16][17][18][19] . Furthermore, attempts to use barcodes to track trays in large nursery production systems have failed as soil and water often covered the barcodes, preventing successful scanning.…”

Section: Introduction mentioning

confidence: 99%

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Comparison of manual and automatic barcode detection in rough horticultural production systems

Eyahanyo

Rath

2019

International Journal of Agricultural and Biological Engineering

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Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success. Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner, and factors such as speed, angle of inclination of the barcode, damage to the barcode and dirt on the barcode. Furthermore, laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming, which leading to reduced productivity. Therefore, an automated image-based barcode detection system to help solve the aforementioned problems was proposed. Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company. The images were analyzed with a specific algorithm developed with the software tool Halcon. Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.

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