LPR/ANPR Guide

By Sean Patton, Published Mar 25, 2021, 01:10pm EDT (Info+)

This 16-page guide explains the fundamentals of license plate recognize / automatic number plate recognition.

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Inside we cover:

  • Traditional OCR LPR
  • OCR Visually Equivalent Characters
  • Deep Learning LPR
  • Plate Datasets
  • Accuracy Claim Issues
  • Machine Learning Detection
  • Detection More Difficult Than Number Recognition
  • Detection Challenges Significant
  • Vehicle Speed
  • Angle Of Plates
  • Damaged Plates
  • Weather
  • Lighting
  • License Plate Variables
  • Mobile and Fixed
  • Dedicated LPR
  • Software Only LPR

This part of our Video Analytics Course starting at the end of March.

LPR/ANPR ********

******* ***** *********** (***) ** ********* Number-Plate *********** (****) ********** **** **** used *** **** ***** ** ****** vehicle ******* ****** *** ****** *** alphanumeric ********** ** *** *****. *** is ******** ******** *** *** ***********, parking, *** ****** ********. ******** ** most ***** ***** *********, *** ********** is **** ******.

***** *** **** ******* ********* *********** (OCR) *** *******, **** ********-***** ********** have *****. *****, * ****** ******** of ******* *** **** ******** **** OCR ** ******.

Two-Step *******

***/**** ******** ** *** *********** *****:

  • **** ***** *** ***** **: ***** surveillance ****** *** ******* **** **********, ranging **** **********, ***********, ******* ***** on ********, ***. *** ****** ***** needs ** ***** **** ********** ** reads ** *** ******* / ****** plates ****.
  • **** *** ********** ** *** *****: Once *** ***** ** *****, *** characters **** ** ** ****, ****** this ** *********** ** ******* ******* including *****, *****, ********** ******, *****/*****, etc.

Traditional *** ***

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*** (******* ********* ***********) ***** * single ********* ** ** *****, *** either ******* ** ******* ******** ********** or ***** *** ********* **** ****** and ******* ***** ****** ******* ******** for **********.

*** ******* '*' ** ******* **** one ****** **** **** **** ** right, *** ****** **** **** ***** to ****, *** * ********** **** in *** ******. ** ******* *** edges ** *** *********, *** ********** it ** ** '*'.

***** ******** ** **** ********* ** changes ** **** *** ****. *******, OCR ********* **** *** **** **** steep ****** ** **** ** ********** characters.

*** ***** **** ** *******-*****, ****** spaced **********, *** ** ******* **** are ******** ** ** **************.

*** *******, ***** ** ****** **** a ****-******** ********** **********, ***** ***** letters, ***** ******* **********, *** ********* designed ********** **** ******* ** ****** differentiate ******* **********:

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******* ********* ****** *** ************ *********** to *** ******* **** ********** *** designed ** **** **** **** ** right, *** *** ***** ** * stacked ********** *** *** ***** ** look **** *** ***** ********* *******:

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OCR ******** ********** **********

* ******* ******** ** *** ********** is **** ********** ** ****** ******* plate ***** **** **** *** ******, in *** ******, ****** *********** (*.*. O ** * ** * (****), S ** *, * ** *, B ** *).

**** ***** **** * ******* ***** with *** ********** "*******" ***** ***** read ** "*******", ** "*******":

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**** ************* ********* *** ********* ** automatically *********** * ******* ***** ** a ***** ****. *********** ******* ********** **** ** ********* ** plates **** *** **********, ****** **** were *******, *** **********, ** *** detected **** ** ****** **********.

** ******* ****, **** *** ********** have *********** ********** ********** ** ******** the **** ** ****** ******* ******, this ** ******** ******** ** ** "fuzzy" ********. *******, **** ********* *** false ******** ****, ***** ** * compliance ***** *** ******** *** *******, because ******** **** ********** ******* ****** will ** ******* ****** ** ***** that ****** *** **** ******.

Pixel ******* ************

******* ***** *********** ************ ******* ** pixel ******* **** ******, *** ***** requiring ***-******, **** ****** **** ****** or ******* *********.

************* ********* ******* ************ ** ****** over *** ****** ** ***** ** the ***** *** ** **********. **** of ******* ****** *** ***** ** vehicles ****** *** ***** ************ *************, as ** **** ******* **** **** ************ ***:

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Deep ******** ***

**** ****** *** ********* *** **** learning ********** ** **** ******. ***** some *** ***** **** ********, **** commercial ********* *** * *********** ** machine ********, **** ********, *** ***:

  • ***** **** ******** (******* *********, **** *** **** ******): ****** ********, ****** ******, *** read **********.
  • **** ******** *** ****** (** ******* *********, **** *** **** Plates): ****** ******, *** **** **********.
  • **** ******** ********* (**** ****** ****): ** ******* *********, ****** ****** then *** *** ** ****

***** **** ******** ******* *** ******* ************** ************ *** ***, ***** **** a *****-**** ******* ** **** ******. Partially **** ******** ********** *** **** learning ** **** ****** *** ****** the ***** *** ***** *** ********, then *** ** **** *** **********:

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*******, ** *** * ****** ************* cost **** ***. **** ** ********** important ** *** ******* **** *** (30 ***+) ** ****** ** **** plates **** ****-****** ****, ************* ******/****/******* **************

**** ******** ** **** ******** **** OCR *** **** ********* ** *********. It ***** ****** **** *******, ***** variation, ******** *******, *** ********* ******.

************, ******* ********** *** **** ** an ***** **** **** *** ******* deep ******** ********** *** ******* *** letters, *** **** ******* *** *****:

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**** ******** *** ** **** ***** bundled **** ***** ********* **** ******* classification (*****, **** *****) *** ******* pattern ********** ******* ********** *******.

Plate ********

**** ******** *** ** ******* ************ ***** ********, ******* ** ***** **** ******** algorithms (*.*.****** ***********), *** ** ********* ********** *** testing *** ***********.

*** ******** ** *, *** ** some ***** ** *** *****, ******* plates *** ********* *******, ******* ******** require ******* ******** *** ********* ** retrain ***** **********.

Accuracy ***** ******

**** *** ************* **** ************ **** **** ******** Rate *** ******** (******* ********* ******** *****), ***** ** *********** ******* ** ignores *** ******* ****** **** ** did *** ******.

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*** *******,****** ** "**%" ******** *********** *** alphanumeric ********** ** * ******* ***** are ******, *** **** ********* ***** only ****** **** **** **** *********** count ******* **** ******** ******, *** plates **** **** *** **** ** all, ***** ** ****** ** *** real-world.

****** ****** **** ***** ****** ****** (vehicle *****, **** ******, *** *******, damaged ******, ******** ******) *** *** counted ******* *** ********, ***** **** not ******* *** ****-***** *********** ** the ******** ******.

Machine ******** *********

***-***** *** **** ******* ******** ** find ******, ***** ******* *********** ** find *** ******** *** ***** ** the ******* *****:

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**** *********** *** **** **** ** detecting ***** *** ***** ** ******* using ********* ******* ***********, **** ********** *********** (**** *****). **** *********** *** ******* ******* and ******** ******* *******, ** **** plates ** ********:

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**** ******* ******** ********* ********** **** pre-programmed ****** *** ******** ******* ***** height *** ***** (*.*. ** ******* plates **** ************* * *:* ***** to ****** *****).*******, ******* ** ****, ******* ******** LPR ** **** **** ** ******* plate-shaped ****, **** ** *** * license *****:

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******* ******** ** *************** ****** **** deep ******** ******* *** ******* ****** used ******* *** **** ************ (*.*. low *****, ****-*** ************) ** ** sufficiently ********.

Detection **** ********* **** ****** ***********

******* ** *** **** ********* ********, detecting ****** ** ********* **** ********* than *********** *** ********** ** ****** that **** **** ********.

**** ** ****** ****** ***********, ***** detection ** **** ****** **** ***********.

Detection ********** ***********

******* ***** ********* ** ********* *********** because ** ** ********* *******, ********* in ************ ******** *** ******* **********, on ****** ********.

*** **** ****** ******* **** ***** LPR ********** ***:

  • ***** ** ******
  • ******* *****
  • ******* ******
  • *******
  • ********
  • ***** *******

Angle ** ******

*** ***** ** ******* ** *** most ********, ************ ****** ** ***. Direct ****** **** ** ****** ******** compared ** ******* ******. **** ******** and ********** ****** ****** ** ** direct ** ****** ******** ** ********.

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******* ** ****, **** ****-***** *** applications ** ******** (*.*. *******) *** mounted ******** ***** *** **** ******* and *** *** ** *** ****.

Damaged / ***** ******

******* ** ***** ****** *** *********** to ******* ******** *** *** *** because ***** ******* **** ** ******* edges. **** ******** ***** ****** **********, missed *****, *** ******* ***** ** detected ******:

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***** **** ******** ********** *** ****** at ******* **** ******* ** ***** plates ******* **** *** *** ******* for *****, ******* *** ***** ****** decrease *** ******* ** *** ***** captured ** *** ******, ********** ********.

*******

***** **** *** ******* ***** ******** performance ** ***** ******* **********; ****, snow, *** *** ************* ****** ***** detection *** ******* ***********, ***** ******* LPR ********* ***********:

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******* ***** ** ******** ********, ****-******* vehicles ****** **** ******* *********** ***, completely ******** ***** ******* ******, *** even ********* ** ********** ******** **** plates:

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Low *** ******* ********

*** ***** *** *** * ***** challenges; ******* ******** **** **********/**********, *** capturing ****** ***** ** **** ******.

*** ******* **** ** ** ****************** ** ***, ***** ***** ****** ***** ******* darker ***** ******* *** ******* ***** visible:

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******* ********* *** *** ***** *** is ********* ****** ******* *****, ********* sufficient *****, *** *** ** **** that *** ******* ******* **** ********:

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License ***** *********

******* ****** **** ****** ********** *** world, **** ********* *****, *********, ********, and ******/***********.

****** ****** ****** ****** ******* (********* white **** ***** *********) *** *** much ****** ** ****:

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** ****** (*.*. ******* *****) ******* more **********, ******** **** ***** ******* and ***** **** *** ** ******* combined, ***** *** ************* ******** ********* accuracy, *** ******** **********:

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***** ** ********* ********** *** ******* with *** **** **********, ******** ****-******* plates, ******** *** ******** ******** ********* with ****/******, *** **** ** *********:

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****** ********* ** ****** ** *** Middle **** **** **** ******** ********* than *****-***** **********, *** ******* ************* higher ********** **** ********.

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Regional ******* *** ******** ***********

**** *********** ** ***/**** ********, ** is ********* ** ***** *** ******* for ***'* ********** ******. **** ** typically ** * *******-**-******* *****. *******, even ****** * ******* ******* *********, if ******* ******* ****** **** ******* have ********* ***** ** ******, ******** could ** ************* ******* (*.*., *******).

Mobile *** ***** ***

*** ** ******* *** ****** *** fixed *************, *******, *** ***** *** challenges *** *******:

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*** ******* ********** ** ****** *** is * ****** ****** ********, ***** complicates ***** *** ***** ** *******. However, *** ***** ******* *** *********** methods *** *** ****.

Dedicated ******* ***

********* ******* *** ******* ******* *********** LPR *******, ********, *** ******* ***** management ******* **** * ****** ************. They *** ***** ******** *** *********** light, ****-*****, *** ****-******* (*.*. *****-**** highway) ************.

***** ******* *** ********* ******** ** niche, ****-********, ****-******* ***** *** *** not ********** ** *** **** ******.

Software **** ***

********-**** ******* ********* ***** *****-****, ******** IP *******, ******** **** **** ******** algorithms *** ***-***** (***** **-***) ************.

********-**** ********* **** ******* *********** ** camera ****** *** **** ********* ******** due ** ************ *******.

Quick ****** ***

***** ****** *** ******* (*****,*******,********) *** ********* ********, *******, *****-******* systems **** ******** **************, *** ***-****** neighborhood ********** ************.

**** *** ********** ******** ** ***** installation ********* ******* ** *** **** of ********* ***** ** ************** *** have ******* ****** *** **** ******* which *** ******* ***** **** *** be ******** *** ******** *** *****.

Wide ***** ****** (***** $*,*** ** $**,***+)

*** ****** ******* ****** **** *** $1,000 ** $**,***+, *** **** ******* impact ***** ***:

  • ****** *******/********** ** **** ******* ** cameras
  • ******** ******** ******* *********
  • *** **** ****** ******** *** ********* with ***-***** ******* ** ** ** - ***** ****** **** ***** (*** - ******), *** ****** ***** *** far **** ********* **** *** ******** and ********.

Comments (4)

** ***** ** ******* ** ******* a ********** ***** ** **** ************ listing ***** *** ** *** **. deep ********, ***** **. *****, ***.

Agree: 7
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Informative
Unhelpful
Funny

**** *******!

*** ****** ****** *** *** *** leading **** ******* ** ***** *******?

Agree
Disagree
Informative
Unhelpful
Funny

*'** **** ***** ***** (********) *** years ******* * *********. ******** ******* for ********** (******, ***** ** ****..** a ***** ** ****) **** ** very ****. ***** ** ** **** model, * **** *** ******* **** and ****** **** *** **** ******** that *** * *** **** ********* to ******.

Agree
Disagree
Informative
Unhelpful
Funny

** **** **** ********* *** ******** (now ********) *** ****** *** *****. The ******* ******* ********* *** ***** nation-wide *** *********** ****-******* ******* (*****) is ****** ** ***. *** ******** is ***** ** ****** ****** ************ but **** ***** **** *** ******* sector ************ **** **** ** ****** that ********* **** * *****-*** ******** to *** *** ****** *** **** to ***** ***** *** **** ** law *********** ** * ******/******* ***********. No **-**** ******* ** **** ****. Entirely *****-*****.

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Informative
Unhelpful
Funny
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