ANALYSIS OF DAMAGED BARCODES
Jennifer Das, Steven Hostetler, Faisal Al-Khalidi, Christopher White, Michael Brockly, Mathia...
Upcoming SlideShare
Loading in...5
×

(Spring 2013) Analysis of Damaged Barcodes

91

Published on

A study on the assessment of two-dimensional barcodes on soil sample bags was conducted by former graduate student Jodi M. Gessner. We used the data she collected to further investigate what is the best bar code label to be used on soil samples so it is still able to be read through different damaging environments. The data that has been previously presented on correction levels 4,5 and 6 and was analyzed on 765 samples.

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
91
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
1
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

(Spring 2013) Analysis of Damaged Barcodes

  1. 1. ANALYSIS OF DAMAGED BARCODES Jennifer Das, Steven Hostetler, Faisal Al-Khalidi, Christopher White, Michael Brockly, Mathias Sutton, Stephen Elliott Overview A study on the assessment of two-dimensional barcodes on soil sample bags was conducted by former graduate student Jodi M. Gessner. We used the data she collected to further investigate what is the best bar code label to be used on soil samples so it is still able to be read through different damaging environments. The data that has been previously presented on correction levels 4,5 and 6 and was analyzed on 765 samples. Problem Determining whether symbology, error correction, location or a combination of the three affects the failure rate of the barcode’s ability to be scanned. Initial Data SYMBOLOGY ERROR CORRECTION LOCATION TOTAL ATTEMPT TOTAL PASS TOTAL FAIL % PASS % FAIL LABEL 1 QR CODE LOW FRONT 145 133 12 91.72% 8.28% LABEL 2 QR CODE LOW SIDE 145 105 40 72.41% 27.59% LABEL 3 QR CODE MEDIUM FRONT 150 141 9 94.00% 6.00% LABEL 4 QR CODE MEDIUM SIDE 150 136 14 90.67% 9.33% LABEL 5 QR CODE HIGH FRONT 140 123 17 87.86% 12.14% LABEL 6 QR CODE HIGH SIDE 150 117 33 78.00% 22.00% LABEL 7 PDF417 4 FRONT 150 145 5 96.67% 3.33% LABEL 8 PDF417 4 SIDE 145 136 9 93.79% 6.21% LABEL 9 PDF417 5 FRONT 145 145 0 100.00% 0.00% LABEL 10 PDF417 5 SIDE 150 141 9 94.00% 6.00% LABEL 11 PDF417 6 FRONT 140 140 0 100.00% 0.00% LABEL 12 PDF417 6 SIDE 145 131 14 90.34% 9.66% LABEL 13 DATA MATRIX NONE FRONT 145 130 15 89.66% 10.34% LABEL 14 DATA MATRIX NONE SIDE 140 128 12 91.43% 8.57% Procedures  Null hypothesis  The proportion of defects for each label is equal.  Alternate hypothesis  At least one proportion is not equal to the rest of the data.  From the initial data, the chi-square test was used to accept or reject the null hypothesis. Chi-square test: Chi-square (Observed value) 129.492 Chi-square (Critical value) 22.362 DF 13 p-value < 0.0001 alpha 0.05  As the computed p-value is lower than the significance level alpha=0.05, we rejected the null hypothesis and accepted the alternative hypothesis.  The Marascuillo procedure was performed to compare each of the barcodes to one another.  The p-values were contrasted and then compared to the critical range to find out if there is a significant difference in the proportion of failed scans to total scans for each barcode.  There were 91 different comparisons performed, 9 of which showed significance. p1 0.082759 p2 0.275862 p3 0.06 p4 0.093333 p5 0.121429 p6 0.22 p7 0.033333 p8 0.062069 p9 0 p10 0.06 p11 0 p12 0.096552 p13 0.103448 p14 0.085714 P-values Conclusion After performing the Marscuillo procedure, we found nine different combinations of symbology, error correction, and locations that are significant. These combinations each show a higher proportions of defects. We can’t state that p2 and p6 are problematic independently, but when contrasted with other variables, they seem to negatively affect the barcode readability. Contrast Value Critical value Significant |p(p2) - p(p3)| 0.216 0.198 Yes |p(p2) - p(p7)| 0.243 0.189 Yes |p(p2) - p(p8)| 0.214 0.199 Yes |p(p2) - p(p9)| 0.276 0.176 Yes |p(p2) - p(p10)| 0.216 0.198 Yes |p(p2) - p(p11)| 0.276 0.176 Yes |p(p6) - p(p7)| 0.187 0.174 Yes |p(p6) - p(p9)| 0.220 0.160 Yes |p(p6) - p(p11)| 0.220 0.160 Yes Significant Comparisons QR Code PDF417 Data Matrix

×