The purpose of this project was to do a comparative analysis of various bar codes on soil bag samples using different scanning methods (more specifically iPhone 5 vs. Android smartphones). This project is also referencing a previous analysis/assessment of the Sure-Tech Laboratories’ soil bags using a regular bar code scanner. Using the samples from the Sure-Tech Laboratories Company, we compared the effectiveness of readability of the bar codes and the data from the regular bar code scanner vs. smartphone technologies.

1. ANALYSIS OF BAR CODES WITH
DIFFERENT SCANNING DEVICES
Ivan Fung, Nick Formoso, Erika Jinbo, David McNutt, Kevin O’Connor, Stephen Elliott
The purpose of this project was to do a comparative analysis of various bar codes on soil bag samples using different scanning methods (more specifically iPhone 5 vs.
Android smartphones). This project is also referencing a previous analysis/assessment of the Sure-Tech Laboratories’ soil bags using a regular bar code scanner. Using
the samples from the Sure-Tech Laboratories Company, we compared the effectiveness of readability of the bar codes and the data from the regular bar code scanner vs.
smartphone technologies.
SAMPLE DESCRIPTION
OVERVIEW
METHODOLOGY
RESULTS AND DATA ANALYSIS EXAMPLES OF FAILED SAMPLES
Factors Levels Remarks
Symbology
QR Code
PDF417
Data Matrix
X-Dimension
14.2 mil (QR Code & Data
Matrix)
7.5 mil (PDF417)
Error
Correction
Level
Low
Medium
High
QR Code (L, M, H)
PDF417 (4,5,6)
Data Matrix (N/A)
Label
Location
Front
Side
Label Number Symbology Error Correction Location
1 QR Code Low Front
2 QR Code Low Side
3 QR Code Medium Front
4 QR Code Medium Side
5 QR Code High Front
6 QR Code High Side
7 PDF417 4 Front
8 PDF417 4 Side
9 PDF417 5 Front
10 PDF417 5 Side
11 PDF417 6 Front
12 PDF417 6 Side
13 Data Matrix N/A Front
14 Data Matrix N/A Side
The samples used for this
analysis are bar codes
printed on soil sample bags
from Sure-Tech Labs. They
were all acquired from a
previous study conducted.
These samples are varied in
three factors: bar code
symbology, error correction
level, and label location.
Table 1 shows an
explanation of the levels.
The samples are then
further categorized into 14
groups. Each label has a
distinct combination of
symbology, error correction
level, and label location.
Table 2 shows the
characteristics of each label
number.
Table 1: Level of details for bar code
symbology, error correction, and label
location
Table 2: Characteristics of each label
number
Figure 4: Data collection process
The phones are clamped into a rig that
keeps the phone exactly 10 cm from the
scan subject. If the phones do not scan the
bar code within 10 seconds, we consider it
a failed attempt.
Both phones used the application called
“Barcode Scanners” by Manatee Works.
Figure 4 shows a flow chart that shows
how we went through and scanned each
bag.
Table 3: Summary of data entry results
Table 3 shows the data we
collected in this research.
Every group of soil bags has
28–30 samples and each
one of them was scanned
five times. We then totaled
the number of successful
scans for every bag within
each group.
Compared to the scanner,
the iPhone and Android had
more 4–5 successful scans
among all bags. But iPhone
and Android also had more
0 successful scans
compared to the scanner.
PDF417 bar codes printed on the front with high error correction had a 100% of
scan pass percentage for all three devices.
iPhone Android Scanner
Label # 0 1-3 4-5 0 1-3 4-5 0 1-3 4-5
1 1 2 26 2 3 24 1 1 27
2 1 0 28 2 1 26 4 9 16
3 1 2 27 1 2 28 0 1 29
4 1 1 28 2 2 26 1 3 26
5 1 7 20 0 0 28 0 11 17
6 2 0 28 2 0 28 1 8 21
7 1 0 29 0 0 30 0 0 30
8 1 1 27 0 1 28 0 3 26
9 0 0 29 3 0 26 0 0 29
10 3 0 27 0 3 27 1 1 28
11 0 0 28 0 0 28 0 0 28
12 7 1 21 9 1 19 1 3 25
13 1 0 28 0 1 28 1 2 26
14 2 1 25 4 1 23 2 0 26
Figure 5: With this QR Code, the scanner, iPhone, and Android
Phone all failed to scan this for the five trials that it was tested.
Figure 5: Sample 1
Figure 6: Sample 2
Figure 6: For this Data Matrix Code, the regular scanner succeeded in
scanning it, but both the iPhone and Android Phone failed to scan it.
Figure 7: Sample 3
Figure 7: For this QR Code, the regular scanner failed to scan it, but
both the iPhone and Android Phone succeeded in scanning it.
Specifications Samsung Galaxy SII
Operating
System
Android 2.3.3 (Gingerbread)
System on
Chip
Samsung Exynos 4 Dual 45 nm (GT-I9100, SHW-M250S/K/L)
CPU 1.2 GHz dual-core ARM Cortex-A9
GPU ARM Mali-400 MP4
Memory 1 GB RAM
Storage 16 GB flash memory
Data Inputs Multi-touch touch screen, headset controls, proximity sensor,
ambient light sensor
Display 4.3 in (110 mm) AMOLED with 480×800 pixels (218 ppi) and RGB-
Matrix
Rear Camera 8 Mpx Back-illuminated sensor with auto focus, 1080p 30 fps full
HD video recording. Single LED flash.
SCANNER DESCRIPTION
Specifications Apple iPhone 5
Operating
System
iOS 6.1
System on
Chip
Apple A6
CPU 1.3 GHz dual core Apple A6
GPU PowerVR SGX543MP3
Memory 1GB LPDDR2-1066 RAM
Storage 16 GB
Data Inputs Touch-screen
Display 4-inch (100 mm) diagonal (16:9 aspect ratio), multi-touch display,
640 × 1,136 pixels at 326 ppi, 800:1 contrast ratio (typical), 500
cd/m2 max. brightness (typical), Fingerprint-resistant oleophobic
coating on front
Rear Camera 8 MP back-side illuminated sensor, HD video (1080p)
Specifications IT4600r Scanner
Symbologies PDF417, MicroPDF417, MaxiCode, Data Matrix, QR
Code, Aztec, Aztec Mesas, Code 49, and EAN UCC
Composite
Interfaces All popular PCs and terminals via keyboard wedge,
keyboard replacement/direct connect, USB
Illumination LEDs 617nm ± 30nm
Aiming (Green LED
Aimer)
526nm ± 30nm
Image VGA, 752x480. Binary, TIFF, or JPEG output
Skew Angle & Pitch
Angle
±40o
Current Draw (Typical
RMS) Green LED Aimer
Input: 5 V, Scanning: 345mA, Idle: 80mA
Figure 1: Samsung Galaxy SII
Figure 2: iPhone 5
Figure 3: IT4600r Scanner
CONCLUSION AND FUTURE
After working with these mobile scanners and seeing how they compared with a scanner you might find at a
check out, we concluded that while the regular scanner may seem better than a smart phone, the smart
phones performed better with higher success rates. There are instances that the barcode was scanned by the
regular scanner successfully, the phones were unable to scan. The regular scanner scored a lot of 1-3’s but the
phones scored more 0’s and 4-5’s more often than the 1-3’s. As technologies in optics improve, so will the
efficiency of scanning barcodes.