US20090224050A1 - Signal processing in barcode reading with a wavelet transformation - Google Patents
Signal processing in barcode reading with a wavelet transformation Download PDFInfo
- Publication number
- US20090224050A1 US20090224050A1 US12/428,746 US42874609A US2009224050A1 US 20090224050 A1 US20090224050 A1 US 20090224050A1 US 42874609 A US42874609 A US 42874609A US 2009224050 A1 US2009224050 A1 US 2009224050A1
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- United States
- Prior art keywords
- wavelet transformation
- noise
- threshold
- signal
- analogue
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10544—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation by scanning of the records by radiation in the optical part of the electromagnetic spectrum
- G06K7/10821—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation by scanning of the records by radiation in the optical part of the electromagnetic spectrum further details of bar or optical code scanning devices
- G06K7/10851—Circuits for pulse shaping, amplifying, eliminating noise signals, checking the function of the sensing device
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
- G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis
Definitions
- the present invention relates to signal processing methods in barcode reading techniques, and more particularly, to a method for processing a digital signal obtained in a barcode reading operation in which a wavelet transformation is applied to the digital signal and a noise threshold is determined for each level of the wavelet transformation so as to filter wide band noise.
- a laser light beam is projected from a barcode reader to a barcode, and light reflected from the barcode is received by a detector.
- An analogue signal is generated from the received reflected light which represents the information encoded in the barcode.
- the analogue signal is converted to a digital signal by an analogue-to-digital (A/D) converter for further processing and decoding.
- A/D analogue-to-digital
- the digital processing stage usually one or more band-passing digital filters are used to reject noise in the signal.
- image based barcode reading such as CCD or CMOS barcode readers.
- the noise in the signal band cannot be rejected by band-passing filters.
- the white noise may degrade the reading performance when the signal gain is small, e.g., if the barcode is located in a distance, or if the resolving power is low.
- the present invention provides a method for processing a digital signal obtained in a barcode reading operation, in which a wavelet transformation is applied to the digital signal.
- a threshold is determined for each level of the wavelet coefficients, and the coefficients are set to be zero if lower than the threshold.
- the digital signal is converted from an analogue signal obtained in the barcode reading operation
- the threshold is a noise threshold determined from information obtained in an analogue processing stage in which the analogue signal is processed before the analogue-to-digital conversion.
- the noise threshold is calculated from a total transfer function H( ⁇ ) in the analogue processing stage:
- Noise ⁇ ⁇ Threshold n 0 ⁇ 2 ⁇ ln ⁇ ( N ) ⁇ 1 2 ⁇ ⁇ ⁇ ⁇ - ⁇ ⁇ ⁇ ⁇ H ⁇ ( ⁇ ) ⁇ 2 ⁇ ⁇ ⁇ ⁇ ( 1 )
- n 0 resistance thermal noise generated in a preamplifier in the analogue signal processing stage
- N is number of data
- the total transfer function H( ⁇ ) is a product of at least one of a transfer function of a differential processing stage H diff , a transfer function of an AGC amplification stage H vagc , and a transfer function of a frequency filtering stage H ⁇ :
- H ( ⁇ ) H diff ⁇ H vagc ⁇ H ⁇ (2)
- the wavelet transformation is a Haar Wavelet transformation.
- the wavelet transformation is a discrete wavelet transformation.
- FIG. 1 is a block diagram schematically illustrating signal processing stages implementing signal processing method in a barcode reading operation according to the present invention.
- FIG. 2 is a block diagram schematically illustrating wavelet noise filter applied to the digital signal in the signal processing method according to the present invention.
- signal processing in a barcode reading operation usually comprises an analogue processing stage 10 and a digital processing stage 20 .
- the analogue processing stage 10 usually comprises a preamplification stage 11 , differential processing stage 12 , gain control amplification (GCA) 13 , frequency filtering 14 , etc.
- GCA gain control amplification
- the analogue signal is converted to a digital signal by an analogue-to-digital (A/D) converter 21 , and the converted digital signal is processed with proper algorithms so as to digitally filter noise, to decode the signal, etc.
- A/D analogue-to-digital
- a wavelet transformation 22 is applied to the digital signal so as to reduce noise, especially wide band noise such as white noise, as explained in more detail below.
- a discrete wavelet transformation can be expressed as
- the discrete wavelet coefficient is:
- a signal is decomposed using the wavelet coefficients at every level.
- a signal ⁇ 0 (t) can be expanded as:
- g 1 (t) is called “wavelet component” of level 1.
- g 1 (t) can be expressed as:
- the signal ⁇ 0 (t) can be expanded to level j as follows:
- White noise does not have coherency with the signal.
- a noise threshold for each level of the wavelet transformation is properly determined, and the coefficients less than the noise threshold are set to be zero. This can reduce wide band noises including white nose. As long as the noise threshold is larger than zero, it is effectual for noise reduction. However, if the noise threshold is too large, it will make a distortion in the signal.
- the noise threshold can be expressed by the following equation:
- ⁇ is standard deviation of noise
- N is number of data
- the standard deviation of noise ⁇ is preferably set to be equal to the noise input n in to wavelet transformation, which is calculated as follows:
- n in n 0 ⁇ 1 2 ⁇ ⁇ ⁇ ⁇ - ⁇ ⁇ ⁇ ⁇ H ⁇ ( ⁇ ) ⁇ 2 ⁇ ⁇ ⁇ ⁇ ( 10 )
- n 0 resistance thermal noise in the preamplifier 11 which is usually the origin of major noises
- H( ⁇ ) is a total transfer function between the preamplifier 11 to wavelet transformation 22 in the analogue processing stage.
- the resistance thermal noise can be calculated from:
- n 0 ⁇ square root over (4 kTR 0 ) ⁇ (11)
- k is Boltzmann constant
- T is absolute temperature
- R 0 is a resistance in the preamplifier 11 .
- the total transfer function H( ⁇ ) is a product of at least one of a transfer function of a differential processing stage H diff , a transfer function of an AGC amplification stage H vagc , and a transfer function of a frequency filtering stage H ⁇ :
- H ( ⁇ ) H diff ⁇ H vagc ⁇ H ⁇ (2)
- Noise ⁇ ⁇ Threshold n o ⁇ 2 ⁇ ln ⁇ ( N ) ⁇ 1 2 ⁇ ⁇ ⁇ ⁇ - ⁇ ⁇ ⁇ ⁇ H ⁇ ( ⁇ ) ⁇ 2 ⁇ ⁇ ⁇ ⁇ ( 1 )
- ⁇ : ⁇ ⁇ H ⁇ ( ⁇ ) H diff ⁇ H vage ⁇ H f ( 2 )
- the wavelet transformation can be a Haar Wavelet transformation or other wavelet transformations.
- transfer functions H diff , H vagc , H ⁇ may be omitted in calculating H( ⁇ ). Therefore, the scope of the present invention is solely intended to be defined by the accompanying claims.
Abstract
A method for processing a digital signal obtained in a barcode reading operation comprises a step of applying a wavelet transformation to the digital signal. The noise threshold at each level of the wavelet transformation is determined from a total transfer function in the analogue processing stage, and the coefficients are set to be zero if less than the noise threshold.
Description
- This application is a divisional application of, and incorporates by reference the entirety of, U.S. patent application Ser. No. 11/253,013, filed Oct. 18, 2005.
- The present invention relates to signal processing methods in barcode reading techniques, and more particularly, to a method for processing a digital signal obtained in a barcode reading operation in which a wavelet transformation is applied to the digital signal and a noise threshold is determined for each level of the wavelet transformation so as to filter wide band noise.
- In a barcode reading operation, a laser light beam is projected from a barcode reader to a barcode, and light reflected from the barcode is received by a detector. An analogue signal is generated from the received reflected light which represents the information encoded in the barcode. After being processed in an analogue processing stage, the analogue signal is converted to a digital signal by an analogue-to-digital (A/D) converter for further processing and decoding. In the digital processing stage, usually one or more band-passing digital filters are used to reject noise in the signal. The similar is true for image based barcode reading such as CCD or CMOS barcode readers.
- However, if there is wide band noise such as white noise, the noise in the signal band cannot be rejected by band-passing filters. The white noise may degrade the reading performance when the signal gain is small, e.g., if the barcode is located in a distance, or if the resolving power is low.
- Therefore, there exists a need for a better method for processing barcode signals so as to eliminate or reduce wide band noise such as white noise.
- To realize the above object, the present invention provides a method for processing a digital signal obtained in a barcode reading operation, in which a wavelet transformation is applied to the digital signal. Preferably, a threshold is determined for each level of the wavelet coefficients, and the coefficients are set to be zero if lower than the threshold.
- Preferably, the digital signal is converted from an analogue signal obtained in the barcode reading operation, and the threshold is a noise threshold determined from information obtained in an analogue processing stage in which the analogue signal is processed before the analogue-to-digital conversion. Preferably, the noise threshold is calculated from a total transfer function H(ω) in the analogue processing stage:
-
- wherein n0 is resistance thermal noise generated in a preamplifier in the analogue signal processing stage, and N is number of data.
- Preferably, the total transfer function H(ω) is a product of at least one of a transfer function of a differential processing stage Hdiff, a transfer function of an AGC amplification stage Hvagc, and a transfer function of a frequency filtering stage Hƒ:
-
H(ω)=H diff ×H vagc ×H ƒ (2) - Preferably, the wavelet transformation is a Haar Wavelet transformation. Preferably, the wavelet transformation is a discrete wavelet transformation.
- The above and other features and advantages will be clearer after reading the detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings, in which:
-
FIG. 1 is a block diagram schematically illustrating signal processing stages implementing signal processing method in a barcode reading operation according to the present invention; and -
FIG. 2 is a block diagram schematically illustrating wavelet noise filter applied to the digital signal in the signal processing method according to the present invention. - As schematically illustrated in
FIG. 1 , signal processing in a barcode reading operation usually comprises ananalogue processing stage 10 and adigital processing stage 20. Theanalogue processing stage 10 usually comprises apreamplification stage 11,differential processing stage 12, gain control amplification (GCA) 13,frequency filtering 14, etc. After being processed in theanalogue processing stage 10, the analogue signal is converted to a digital signal by an analogue-to-digital (A/D)converter 21, and the converted digital signal is processed with proper algorithms so as to digitally filter noise, to decode the signal, etc. - According to the teachings of the present invention, a
wavelet transformation 22 is applied to the digital signal so as to reduce noise, especially wide band noise such as white noise, as explained in more detail below. - A discrete wavelet transformation can be expressed as
-
- The discrete wavelet coefficient is:
-
- wherein j is called a “level”.
- As schematically illustrated in
FIG. 2 , a signal is decomposed using the wavelet coefficients at every level. - The approximate function ƒj(t) at level j is:
-
- wherein s is called a “scale function”.
- A signal ƒ0(t) can be expanded as:
-
ƒ0(t)=ƒ1(t)+g 1(t) (6) - wherein g1(t) is called “wavelet component” of
level 1. - g1(t) can be expressed as:
-
- Thus, the signal ƒ0(t) can be expanded to level j as follows:
-
- White noise does not have coherency with the signal. To reduce noise, a noise threshold for each level of the wavelet transformation is properly determined, and the coefficients less than the noise threshold are set to be zero. This can reduce wide band noises including white nose. As long as the noise threshold is larger than zero, it is effectual for noise reduction. However, if the noise threshold is too large, it will make a distortion in the signal.
- The noise threshold can be expressed by the following equation:
-
Noise Threshold=σ√{square root over (21n(N))} (9) - wherein σ is standard deviation of noise, and N is number of data.
- According to the teaching of the present invention, the standard deviation of noise σ is preferably set to be equal to the noise input nin to wavelet transformation, which is calculated as follows:
-
- wherein n0 is resistance thermal noise in the
preamplifier 11 which is usually the origin of major noises, and H(ω) is a total transfer function between thepreamplifier 11 towavelet transformation 22 in the analogue processing stage. - The resistance thermal noise can be calculated from:
-
n 0=√{square root over (4kTR 0)} (11) - wherein k is Boltzmann constant, T is absolute temperature, and R0 is a resistance in the
preamplifier 11. - Preferably, the total transfer function H(ω) is a product of at least one of a transfer function of a differential processing stage Hdiff, a transfer function of an AGC amplification stage Hvagc, and a transfer function of a frequency filtering stage Hƒ:
-
H(ω)=H diff ×H vagc ×H ƒ (2) - In the barcode reader system illustrated in
FIG. 1 , only the transfer function Hvagc of theGCA amplification 13 is a variable function, and the transfer functions Hdiff and Hƒ are fixed or known functions for calculation by theCPU 23. - Therefore, concluded from the above, the optimum noise threshold is expressed as follows:
-
- Though the above has described the preferred embodiments of the present invention, it shall be understood that numerous adaptations, modifications and variations are possible to those skilled in the art without departing the gist of the present invention. For example, the wavelet transformation can be a Haar Wavelet transformation or other wavelet transformations. When properly, one or more of transfer functions Hdiff, Hvagc, Hƒ may be omitted in calculating H(ω). Therefore, the scope of the present invention is solely intended to be defined by the accompanying claims.
Claims (4)
1. A method for processing a digital signal obtained in a barcode reading operation, comprising the steps of applying a wavelet transformation to said digital signal; determining a threshold for coefficients for each level in said wavelet transformation, and setting said coefficients as zero if lower than said threshold.
2. The method of claim 1 , further comprising a step of determining a threshold for coefficients for each level in said wavelet transformation, and setting said coefficients as zero if lower than said threshold.
3. A method of reducing white noise from an analogue signal obtained in a barcode reading operation, comprising the steps of:
converting said analogue signal to a digital signal;
applying a wavelet transformation to said digital signal;
determining a noise threshold for each level in said wavelet transformation; and
setting all coefficients of said wavelet transformation to be zero if lower than said noise threshold.
4. The method of claim 4 , wherein said noise threshold is determined based on information obtained in an analogue processing stage for processing said analogue signal.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US12/428,746 US20090224050A1 (en) | 2005-10-18 | 2009-04-23 | Signal processing in barcode reading with a wavelet transformation |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/253,013 US7526130B2 (en) | 2005-10-18 | 2005-10-18 | Signal processing in barcode reading with a wavelet transformation |
US12/428,746 US20090224050A1 (en) | 2005-10-18 | 2009-04-23 | Signal processing in barcode reading with a wavelet transformation |
Related Parent Applications (1)
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US11/253,013 Division US7526130B2 (en) | 2005-10-18 | 2005-10-18 | Signal processing in barcode reading with a wavelet transformation |
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US20090224050A1 true US20090224050A1 (en) | 2009-09-10 |
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US11/253,013 Expired - Fee Related US7526130B2 (en) | 2005-10-18 | 2005-10-18 | Signal processing in barcode reading with a wavelet transformation |
US12/428,746 Abandoned US20090224050A1 (en) | 2005-10-18 | 2009-04-23 | Signal processing in barcode reading with a wavelet transformation |
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US11/253,013 Expired - Fee Related US7526130B2 (en) | 2005-10-18 | 2005-10-18 | Signal processing in barcode reading with a wavelet transformation |
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US (2) | US7526130B2 (en) |
JP (1) | JP2009512093A (en) |
DE (1) | DE112006003048T5 (en) |
WO (1) | WO2007047550A2 (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110297748A1 (en) * | 2009-01-15 | 2011-12-08 | Eth Zurich | Method and portable apparatus for recognizing bar codes |
CN108985179A (en) * | 2018-06-22 | 2018-12-11 | 福建和盛高科技产业有限公司 | A kind of electric energy quality signal denoising method based on improvement wavelet threshold function |
Families Citing this family (6)
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US7804945B2 (en) * | 2005-08-31 | 2010-09-28 | Accenture Global Services Gmbh | Enterprise application based multi-billing integration system |
US7526130B2 (en) * | 2005-10-18 | 2009-04-28 | Optoelectronics Co., Ltd. | Signal processing in barcode reading with a wavelet transformation |
US8150163B2 (en) * | 2006-04-12 | 2012-04-03 | Scanbuy, Inc. | System and method for recovering image detail from multiple image frames in real-time |
US9038917B2 (en) | 2012-02-01 | 2015-05-26 | Optoelectronics Co. Ltd. | System and method for noise reduction in a bar code signal |
WO2013151536A1 (en) | 2012-04-03 | 2013-10-10 | Optoelectronics Co., Ltd. | Variable gain amplifier for bar code reader |
CN109035538A (en) * | 2018-10-16 | 2018-12-18 | 深圳美特优科技有限公司 | A kind of visiting personnel registration checking device based on recognition of face |
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-
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- 2006-10-13 WO PCT/US2006/040299 patent/WO2007047550A2/en active Application Filing
- 2006-10-13 DE DE112006003048T patent/DE112006003048T5/en not_active Ceased
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2009
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CN108985179A (en) * | 2018-06-22 | 2018-12-11 | 福建和盛高科技产业有限公司 | A kind of electric energy quality signal denoising method based on improvement wavelet threshold function |
Also Published As
Publication number | Publication date |
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WO2007047550A3 (en) | 2008-07-31 |
WO2007047550A2 (en) | 2007-04-26 |
US7526130B2 (en) | 2009-04-28 |
JP2009512093A (en) | 2009-03-19 |
US20070086670A1 (en) | 2007-04-19 |
DE112006003048T5 (en) | 2008-10-09 |
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