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Barcode/label detection

asked 2019-02-05 10:24:59 -0500

FreddyB gravatar image

updated 2019-02-05 10:50:35 -0500

I am learning opencv with the hope of developing a python program that will detect labels and identify numbers on cotton bales from a video camera mounted on a forklift. With what I have learned so far, I am assuming that the best way would be to use a haar cascade to detect and extract the label from the image, then implement some other library to decode a bar code or use ocr to read the numbers on the label.

My question(s) are:

  • Is my assumption correct that haar cascade is the best way
  • What kind of images would be best to train the cascade? My concern is that it will only detect the numbers that were used to train the cascade.
  • I do have the ability to change the label. Is there a change that would make the label easier to detect?
  • Is OCR number reading better/easier/more reliable than decoding bar codes or vice-versa

Any other advice or direction would be greatly appreciated. I am attaching pictures of bales and label. Thanks in advance.

C:\fakepath\bales.jpg

C:\fakepath\label.jpg

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answered 2019-02-05 17:27:49 -0500

updated 2019-02-05 18:02:51 -0500

i think Cascade classifier is not suitable.you can try digits_video.py for some ideas.

take a look at the image below to see some results if you can do right segmentation of digits

image description

you can get the image above by adding

frame = cv.imread("15494095161414931.jpg")

at line 39

using the image below which i manually cropped digits and resized 2.5x from your image to show just an idea to start (you need to improve )image description

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Thank you. Most helpful.

FreddyB gravatar imageFreddyB ( 2019-02-07 21:07:43 -0500 )edit
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answered 2019-02-05 13:55:08 -0500

I work in the barcode scanner industry. Some thoughts.

There is no one best detection+decode method; it depends on application needs: time, CPU, RAM, camera performance, co-processing, frame rate, pose of labels, etc. Researching public implementations and papers may educate you and save you time. Keep an open mind, keep your techniques simple.

Note: I haven't employed machine learning for detecting presence of or decoding barcodes.

Labels need to be big enough to be easily detected and decode elements with high contrast, not over/under printed, correctly illuminated, etc. In your multiple bale image, labels are too small with light reflections.

OCR reading: in general, it's hard to find and decode. Barcodes were designed to be easy to be detected/decoded reliably and naively.

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Asked: 2019-02-05 10:24:59 -0500

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Last updated: Feb 05 '19