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Introduction
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In this article, you will find additional information and best practices for data capture with Anyline. For any comments or questions, please get in touch with your contact person at Anyline. |
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General Quality Drivers
Environmental Conditions
Challenging environmental conditions and tire degradations can lead to a suboptimal scanning performance. This can be reflected through lower scan accuracy or a longer time needed to complete a successful scan result. Below, you will find a list of the most common factors which can be the cause of suboptimal scanning performance.
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Conditions and Factors | Correct Practice | Incorrect Practice |
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Low Lighting Conditions Low light reduces the contrast of the image, making it harder to separate the characters from the background. Additionally, the phone camera will compensate for the low light by increasing the sensitivity of the sensor (ISO) and exposure, which raises noise and motion blur on the image. Try using external light sources or even turn on the flashlight on your device (if available). |  |  |
DOT/TIN Example | ||
Worn Tires / Abrasion If a tire is scraped or damaged, characters may be faded or no longer visible. In both cases, this can lead to OCR misclassification*. In case of worn tires, double-check if the characters can be read with a human eye first. |  |  |
Tire Size Example | ||
Cutout Position Our Scanner performs the best with all the characters aligned within the centre of the cutout. Any characters beyond the border of the cutout will hinder the scanning performance and cause the results to be less accurate. |  |  |
Tire Make Example | ||
Focus Any image with little to no focus in the shot will either result in an inconclusive scan or an inaccurate reading. To avoid this, please ensure that your camera is focused on the characters with every part of the scannable object being clear and readable. |  |  |
Tire Commercial ID Example | ||
Dirt Dirt can affect the scanner in various ways. If dirt partially or fully covers characters, they may be misread, or not detected at all (no result). In that case, try to remove the dirt from the tire and scan again. |  |  |
Tire Model Example | ||
High or Low Angles To achieve more accurate results and a better overall scanning experience, align your device so that the camera of choice is directly in line with the scannable item. If the angle is too low or too high, the characters may not be as clear for the scanner to get an accurate read. Also, avoid using angles where any textured backgrounds could surround the scannable area. |  |  |
DOT/TIN Example | ||
Reflection Reflection may cause multiple problems, including over-exposure which lowers contrast, or full occlusion of certain parts of the tire. This can lead to OCR misclassification and/or incorrect scan results. In that case, try to improve the light conditions (different or additional light source, blocking direct sun) and scan again. | %20Example.jpg?version=1&modificationDate=1687423841771&cacheVersion=1&api=v2) |  |
Tire Size Example | ||
NOTE - For Worn Tires / Abrasion:
Background texture recognition improved after v37.
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Hardware Related Quality Drivers
Accuracy can also be negatively influenced by a number of factors relating to the device being used (e.g. the camera quality). Below, you will find the most important properties to consider when selecting your scanning device.
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Another important factor to consider, which can lead to a suboptimal scanning performance and influence user experience, is the processing power of the device. The more processing power available, the more computer vision and machine learning operations can be performed per second. |
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Links to Documentation
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If you require any further information or details on our Tire Scanning Module, |
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Glossary
Please Note:
*OCR misclassification - Refers to the reading of a character/number and incorrectly classifying it as another number (e.g., 1 instead of 7, “O” instead of 0, etc.)
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