KR20170108646A - Appratus and method of noise relieving using noise tolerant optical detection in coms image sensor based visible light communication - Google Patents

Abstract

The present invention relates to a noise mitigation technique using a noise-tolerant light reception technique in a CMOS image sensor-based visible light communication method. A noise mitigation device according to one aspect includes a calculation unit configured to calculate a noise average value for the signal value of the extracted frame, and a background removal unit configured to remove a background of the signal value based on the calculated average value, and a normalization unit for processing unit configured to normalize the signal value from which the background is removed.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a noise cancellation method and a noise cancellation method,

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a noise mitigation technique using a noise immunity light reception technique in a visible light communication method based on a CMOS image sensor.

Visible light communication is a communication technology that transmits information using visible light (400 to 700 nm).

This kind of visible light communication is a technology that sends information by blinking visible light of a light emitting diode (LED) used in a light emitted from a fluorescent lamp or a display device at an invisible speed. It is a power line communication (PLC) To connect the lighting equipment to the Internet, and to connect to the Internet. In particular, visible light communication is more secure than wireless LAN because there is no fear that information will leak outdoors when the light is blocked, and the use of several computers at the same time is not significantly reduced. In addition, the visible light communication can communicate even at the LED illuminance which can not be seen by the naked eye, and there is no problem such as frequency crosstalk, and it is possible to provide the high-speed communication service at low cost, to replace the public WI-FI, It is being evaluated as a technology.

However, despite the advantages of visible light communication, additional devices have to be used to apply the visible light communication technology to the smartphone, and there are difficulties in data communication under the noise (interference light, reflected light, etc.) .

Korean Patent No. 10-1225056 Korean Patent Publication No. 10-2012-0016571

A noise mitigation apparatus according to one aspect includes a calculation unit that calculates a noise average value of a signal value of an extracted frame, a background removal unit that removes a background of the signal value based on the calculated average value, And a normalization processor for processing the normalization of the signal value.

The calculating unit according to an embodiment calculates the noise average value based on an average value of each column for the signal value.

The background removal unit removes a high frequency component of the signal value and extracts an approximate curve of a background value of the signal value from which the high frequency component is removed.

The background removing unit according to an embodiment removes the high frequency component through a low pass filter.

The background removal unit extracts an approximate curve for the background value using a polynomial curve fitting.

The normalization processing unit performs the normalization process on the signal value based on a ratio of an approximation curve equal to or greater than the normalization reference value and a difference value about the approximation curve equal to or less than the normalization reference value.

An image sensor according to one side includes an extracting unit for extracting a frame value from the generated image, a noise mitigating unit for mitigating noise based on an average value of each column of the signal value extracted from the extracted frame value, A data packet extracting unit for extracting a data packet from the extracted data packet, and a data extracting unit for extracting data from the extracted data packet.

The noise mitigation unit according to an embodiment removes the background for the signal value based on the calculated average value and processes the normalization for the signal value from which the background is removed to alleviate the noise.

The noise mitigation unit according to an exemplary embodiment removes a high frequency component of the signal value and extracts an approximate curve of a background value of the signal value from which the high frequency component is removed.

The noise mitigation unit according to an exemplary embodiment removes the high frequency component through a low pass filter and extracts an approximate curve for the background value using a polynomial curve fitting.

The noise mitigation unit performs the normalization process on the signal value based on a ratio of an approximate curve that is equal to or greater than a normalization reference value and a difference value to an approximate curve that is equal to or less than the normalization reference value.

A noise mitigation method according to one aspect includes the steps of: calculating a noise average value of a signal value of an extracted frame; removing a background of the signal value based on the calculated average value; And processing the normalization.

The calculating step according to an embodiment includes calculating the noise average value based on an average value of each column for the signal value.

The removing of the background according to an exemplary embodiment includes removing a high frequency component of the signal value and extracting an approximate curve of the background value of the signal value from which the high frequency component is removed.

The removing of the background according to an embodiment includes removing the high frequency component through a low pass filter and extracting an approximate curve for the background value using Polynomial Curve fitting .

The step of processing the normalization according to an exemplary embodiment includes performing the normalization process on the signal value based on a ratio of an approximate curve equal to or greater than a normalization reference value and a difference value about an approximate curve equal to or less than the normalization reference value do.

1 is a diagram illustrating an overall system to which a noise mitigation apparatus according to an embodiment is applied.
2 is a view for explaining an image and a reception form of a moving picture frame.
3 is a diagram for explaining a signal value before applying the noise reduction processing procedure and a signal value after application.
4 is a block diagram illustrating a noise mitigation apparatus according to an embodiment.
5 is a diagram for explaining a signal value before applying noise average value calculation (noise division) and a signal value after application.
6 is a diagram for explaining a signal value before applying background subtraction and a signal value after application.
7 is a diagram for explaining an approximate curve for zero or more and an approximate curve for a value less than zero.
8 is a diagram for explaining a signal value before and after applying the normalization.
9 is a view for explaining an image sensor according to an embodiment.
10 is a flowchart illustrating a noise mitigation method according to an embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the rights is not limited or limited by these embodiments. Like reference symbols in the drawings denote like elements.

The terms used in the following description are chosen to be generic and universal in the art to which they are related, but other terms may exist depending on the development and / or change in technology, customs, preferences of the technician, and the like. Accordingly, the terminology used in the following description should not be construed as limiting the technical thought, but should be understood in the exemplary language used to describe the embodiments.

Also, in certain cases, there may be a term chosen arbitrarily by the applicant, in which case the meaning of the detailed description in the corresponding description section. Therefore, the term used in the following description should be understood based on the meaning of the term, not the name of a simple term, and the contents throughout the specification.

1 is a diagram illustrating an entire system 100 to which a noise mitigation apparatus according to an embodiment is applied.

The overall system 100 includes a transmitting device 110 for transmitting signals and a receiving device 120 for receiving transmitted signals.

The transmitting-side apparatus 110 can transmit a coded signal transmitted through an American Wire Gage (AWG) to the receiving-side apparatus 120 through the LED module.

The LED module is driven by a DC voltage and may include an amplifier for amplifying a coded signal, a bias tee for applying a DC voltage to the amplified signal, and an LED for emitting a signal corresponding to a DC voltage applied signal have.

Bias tees are used to apply DC power for the operation of active elements such as transistors, field effect transistors (FET), laser diodes, etc., so that the bias circuit can maintain a low impedance and high impedance so that the attachment of the bias circuit does not affect the original high- It can be designed and designed to be detachable so that it can be replaced as needed.

On the other hand, the light from the LED can be diffused through the diffuser lens and transmitted to the receiving-side device 120.

The receiving-side apparatus 120 can receive the diffused emission signal and extract the data.

For example, the receiving-side apparatus 120 may be interpreted as a portable terminal equipped with a photographing module such as a smart phone.

The receiving-side apparatus 120 can capture an image of the diffused light emission signal, and can extract data from the generated image. To this end, the receiving-side apparatus 120 can photograph the light-emitting signal diffused through the photographing means. For example, a smartphone can generate an image based on a light emission signal diffused through a moving picture shooting mode.

Next, the receiving-side apparatus 120 can extract a frame value from the generated image. In addition, the noise can be alleviated based on the average value of the respective columns of the signal values extracted from the extracted frame values. The receiving-side apparatus 120 according to an embodiment can increase the efficiency of noise mitigation by using values obtained by averaging the values of the received signals, rather than the values of one row.

Next, the receiving-side apparatus 120 can extract the data packet from the noise-reduced signal value and extract the data from the extracted data packet.

2 is a view for explaining an image and a reception form of a moving picture frame.

As shown at 200, one frame of a moving picture is composed of a row of 1920 lines and a column of 1080 lines. One frame of the moving picture may include bright and dark portions, which can be expressed by brightness values of each pixel as shown in FIG.

3 is a diagram for explaining a signal value before applying the noise reduction processing procedure and a signal value after application.

Reference numeral 310 denotes a brightness value for each pixel of one frame of the moving picture. In one frame of the moving picture shown in FIG. 2, 1080 lines corresponding to each column may correspond to pixels. That is, reference numeral 310 can be interpreted as a value obtained by averaging brightness values for each column, rather than values of each row, of the received signal (one frame of the moving image). For example, in the present invention, a value of a received signal is referred to as picture (1, x), picture (2, x), ... picture (1, mean (1: 1920)), picture (2, mean (1: 1920)), and picture picture (1080, mean (1: 1920)).

Reference numeral 320 denotes a noise reduction technique according to an exemplary embodiment of the present invention, which is applied to a graph of a reference numeral 310. The reference numeral 320 denotes a noise reduction technique that mitigates noise in a captured moving image and provides a high data transmission rate and a low bit error rate ) To extract the data.

In addition, when data is extracted through a noise canceled signal 320 as shown in reference numeral 320, it is possible to receive a signal from a light source even in an environment in which light other than the light source that generates a signal to the image sensor enters.

Hereinafter, the operation of the noise reduction apparatus for extracting the reference numeral 320 through noise reduction on the graph 310 will be described in detail

4 is a block diagram illustrating a noise mitigation apparatus 400 according to an embodiment.

The noise canceller 400 mitigates noise in a captured moving image, extracts data through a high data rate and a low bit error rate (BER), and extracts data through a noise-reduced signal It is possible to receive a signal from a light source even in an environment in which light other than a light source that generates a signal to the image sensor enters.

To this end, the noise mitigation apparatus 400 according to one embodiment includes a calculation unit 410, a background removal unit 420, and a normalization processing unit 430.

Specifically, the noise mitigation apparatus 400 may include a calculation unit 410, a background removal unit 420, and a normalization processing unit 430. The noise mitigation device 400 may be implemented at least temporarily by the computing terminal. The computing terminal includes any type of electronic device such as a personal computer, a medical device, a smart phone, a tablet computer, and a wearable device. The calculation unit 410, the background removal unit 420, and the normalization processing unit 430 may be physical and / or logical elements included in such electronic devices, respectively. For example, the calculation unit 410, the background removal unit 420, and the normalization processing unit 430 may be implemented by dedicated hardware or general purpose computing resources controlled by software or an operating system. Also, the calculation unit 410, the background removal unit 420, and the normalization processing unit 430 may be implemented together on one chip, and thus may not be physically separated. It can be changed by any change. Accordingly, it is understood that the functions, operations and structures of the calculation unit 410, the background removal unit 420, and the normalization processing unit 430 are distinguished from each other, but there may be cases where such a classification is interpreted differently according to the embodiment.

More specifically, the calculation unit 410 according to an exemplary embodiment calculates a noise average value with respect to a signal value of the extracted frame.

A frame for noise cancellation can be extracted from each frame of the photographed moving image. Accordingly, the calculation unit 410 can calculate a noise average value of the brightness values of the respective columns constituting the extracted frame. At this time, each frame may include a column of 1080 lines, and a brightness value for each column may correspond to a signal value.

5 is a diagram for explaining a signal value before applying noise average value calculation (noise division) and a signal value after application.

Reference numeral 510 denotes a brightness value of each pixel for one frame of the moving picture. In the frame of the moving picture, 1080 lines corresponding to each column may correspond to pixels. That is, reference numeral 510 can be interpreted as a value obtained by averaging brightness values of respective columns, rather than the values of the respective lines, of the received signal (one frame of the moving image). For example, in the present invention, a value of a received signal is referred to as picture (1, x), picture (2, x), ... picture (1, mean (1: 1920)), picture (2, mean (1: 1920)), and picture picture (1080, mean (1: 1920)).

Meanwhile, the calculating unit 410 may extract a reference numeral 520 by calculating a noise average value on a graph 510.

By calculating a noise average value as shown by reference numeral 520, it is possible to extract data through a high data transmission rate and a low bit error rate (BER) by alleviating noise in a captured moving image. In addition, when data is extracted through a noise-reduced signal, it is possible to receive a signal from a light source even in an environment in which light other than the light source that generates a signal to the image sensor enters.

Referring back to FIG. 4, the background removal unit 420 according to the embodiment may remove the background of the signal value based on the calculated average value. Specifically, the background removal unit 420 may remove the high-frequency component of the signal value and extract an approximate curve to the background value of the high-frequency component-removed signal value.

Generally, in motion picture, motion of background is relatively slow and motion of object is relatively faster than motion of a subject. That is, since the signal value changes more than the background value, it has more high frequency components. Therefore, the background removing unit 420 cuts out a signal value of a high frequency component by using a low-pass filter in a frame, and calculates an approximate curve for a background value using a polynomial curve fitting Can be extracted. That is, the background removing unit 420 approximates and removes the background value using polynomial curve fitting from the signal value from which high frequency components have been removed.

The approximation curve can be interpreted as a curve with the reference value of the signal at the signal value and the median values for the maximum (or minimum) value of the amplitude.

6 is a diagram for explaining a signal value before applying background subtraction and a signal value after application.

The background removal unit 420 may generate the signal value 620 from which the high frequency component has been removed by removing the high frequency component of the signal value 610 representing the noise mean value.

In addition, the background removal unit 420 may extract an approximate curve for the background value from the signal value 620 from which the high-frequency component has been removed.

The approximation curve can be interpreted as a curve with the reference value of the signal at the signal value and the median values for the maximum (or minimum) value of the amplitude.

7 is a diagram for explaining an approximate curve for zero or more and an approximate curve for a value less than zero.

As shown in FIG. 7, the background removal unit 420 may determine the normalization reference value to be zero. Thus, the approximate curve A can be interpreted as signals having a size of 0 or more in the background-removed signal, and the approximate curve B can be interpreted as signals having a size of 0 or less in the background-removed signal.

Thus, two different curves between pixel-by-pixel amplitudes can be interpreted as approximate curves. Specifically, the approximate curve A on the graph 700 can be interpreted as an approximate curve for the maximum amplitude and the normalized reference value (0), and the approximate curve B located below the approximate curve A can be interpreted as the minimum amplitude and the normalized reference value 0). ≪ / RTI >

Next, the normalization processing unit 430 according to an exemplary embodiment may process the normalization on the signal values whose background is removed.

For this purpose, the normalization processing unit 430 can perform normalization processing on the signal value based on a ratio of an approximate curve equal to or greater than the normalization reference value and a difference value about the approximate curve equal to or less than the normalization reference value.

For example, assuming that a signal value is S, an approximation curve of a normalization reference value or more is A, and an approximation curve of a normalization reference value or less is B, the signal values can be normalized by the following equation (1).

[Equation 1]

8 is a diagram for explaining a signal value 810 before applying normalization and a signal value 820 after applying normalization.

The signal value 810 before the normalization is applied can be interpreted as a signal value in which the background is removed after a noise value division (noise division) is applied to the signal value for one frame.

More specifically, the signal value 820 is normalized by the normalization processor 430. More specifically, the signal value 820 is an approximation curve A that is equal to or larger than the normalization reference value and an approximation curve B that is equal to or smaller than the normalization reference value (AB) < / RTI >

As a result, by using the noise canceller 400, data can be extracted through a high data transmission rate and a low bit error rate (BER) by reducing noises in the captured moving image, and a noise- It is possible to receive a signal from a light source even in an environment in which light other than a light source that generates a signal to the image sensor enters the image sensor.

9 is a view for explaining an image sensor 900 according to an embodiment.

The image sensor 900 according to an exemplary embodiment may include an extraction unit 910, a noise mitigation unit 920, a data packet extraction unit 930, and a data extraction unit 940.

First, the extraction unit 910 can extract a frame value from the generated image.

Next, the noise mitigation unit 920 can alleviate the noise based on the average value of the respective columns of the signal values extracted from the extracted frame values.

For example, the noise mitigating unit 920 may remove the background of the signal value based on the calculated average value, and process the normalization of the background-removed signal value to mitigate the noise. To this end, the noise mitigation unit 920 may remove the high-frequency component of the signal value and extract an approximate curve to the background value of the high-frequency component-removed signal value. In addition, the noise mitigating unit 920 can remove the high-frequency component through the low-pass filter and extract an approximate curve for the background value using a polynomial curve fitting. In particular, the noise mitigation unit 920 may perform normalization processing on the signal value based on a ratio of an approximation curve equal to or greater than the normalization reference value and a difference value about the approximation curve equal to or less than the normalization reference value.

Next, the data packet extracting unit 930 extracts the data packet from the noise-reduced signal value, and the data extracting unit 940 extracts the data from the extracted data packet.

The use of the image sensor 900 according to an embodiment of the present invention mitigates noise in a captured moving image to enable data extraction through a high data transmission rate and a low bit error rate (BER) When extracting data through a signal, it is possible to receive a signal from a light source even in an environment in which light other than a light source that generates a signal to the image sensor enters.

10 is a flowchart illustrating a noise mitigation method according to an embodiment.

The noise mitigation method according to an exemplary embodiment may extract a frame value (step 1001). In the present invention, a frame value is a signal value for an extracted frame, and can be interpreted as brightness values for each column of the frame.

Next, the noise mitigation method may calculate a noise average value for the brightness values, i.e., the frame values, for each column of the frame (step 1002). At this time, the noise mitigation method can improve the noise mitigation efficiency by using the value of the received signal, that is, the value obtained by averaging each column instead of the value of one row of the frame value. For example, the noise mitigation method may calculate a noise average value for the brightness values for each of the columns constituting the extracted frame. At this time, each frame may include a column of 1080 lines, and a brightness value for each column may correspond to a signal value.

The noise reduction method according to an exemplary embodiment may process background removal for a frame value in which a noise average value is calculated (step 1003). Specifically, the noise reduction method uses a low-pass filter in the frame to cut out most high-frequency signal values and uses an approximate curve for the background value using a polynomial curve fitting Can be extracted.

The noise mitigation method according to an exemplary embodiment may perform the normalization process using the extracted approximate curve and the background-removed signal values (step 1004).

For example, assuming that the normalization reference value is 0, assuming that the signals having a size of 0 or more in the background-removed signal are approximate curves A, signals having a size of 0 or less in the background- .

That is, the approximate curve A can be interpreted as an approximate curve for the maximum amplitude and the normalized reference value (0), and the approximate curve B positioned below the approximate curve A can be interpreted as an approximate curve for the minimum amplitude and the normalized reference value .

In this case, the noise mitigation method according to the embodiment is based on the ratio S / (AB) of the difference value AB with respect to the signal value S with respect to the approximate curve equal to or greater than the normalization reference value and the approximate curve equal to or less than the normalization reference value So that the noise can be mitigated.

Next, the noise mitigation method according to an exemplary embodiment extracts a data packet for a noise-mitigated signal (step 1005), and extracts data from the extracted data packet (step 1006).

As a result, by using the present invention, VLC (Visible light communication) can be realized without attaching additional equipment by directly utilizing a CMOS image sensor built in a smart phone. That is, VLC (Visible light communication) can be realized without using a photodiode as a receiver. In addition, it is possible to perform data communication under the conditions such as interference light or reflected light, which may occur in an actual communication environment, and to reduce noise, thereby achieving a higher data transmission rate and a lower bit error rate (BER, error rate. < / RTI >

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (16)

A calculation unit for calculating a noise average value of signal values of the extracted frames;
A background removing unit configured to remove a background of the signal value based on the calculated average value; And
A normalization processing unit for processing normalization of the signal value from which the background is removed,
/ RTI > The method according to claim 1,
The calculating unit calculates,
And calculates the noise average value based on an average value of each column for the signal value. The method according to claim 1,
The background removal unit may include:
And extracts an approximate curve with respect to a background value of the signal value from which the high frequency component is removed. The method of claim 3,
The background removal unit may include:
And removes the high-frequency component through a low-pass filter. The method of claim 3,
The background removal unit may include:
A noise mitigation device for extracting an approximate curve for the background value using a polynomial curve fitting. The method according to claim 1,
The normalization processing unit,
And performs the normalization process on the signal value based on a ratio of an approximate curve equal to or greater than a normalization reference value and a difference value about an approximate curve equal to or less than the normalization reference value. An extracting unit for extracting a frame value from the generated image;
A noise mitigator for mitigating noise based on an average value of each column of signal values extracted from the extracted frame values;
A data packet extracting unit for extracting a data packet from the noise-reduced signal value; And
A data extracting unit for extracting data from the extracted data packet,
. 8. The method of claim 7,
Wherein the noise-
And removing the background for the signal value based on the calculated average value and processing the normalization for the signal value from which the background is removed to alleviate noise. 8. The method of claim 7,
Wherein the noise-
And extracts an approximate curve for the background value of the signal value from which the high-frequency component has been removed. 8. The method of claim 7,
Wherein the noise-
Removing the high-frequency component through a low-pass filter,
An image sensor for extracting an approximate curve for a background value using a polynomial curve fitting. 8. The method of claim 7,
Wherein the noise-
And performs the normalization processing on the signal value based on a ratio of an approximate curve equal to or greater than the normalization reference value and a difference value about the approximate curve equal to or less than the normalization reference value. A noise mitigation method implemented at least temporarily by a computer,
Calculating a noise average value of a signal value of the extracted frame;
Removing a background of the signal value based on the calculated average value; And
Processing the normalization for the signal value from which the background has been removed
/ RTI > 13. The method of claim 12,
Wherein the calculating step comprises:
Calculating the noise average value based on an average value of each column for the signal value
/ RTI > 13. The method of claim 12,
The step of removing the background comprises:
Removing a high frequency component of the signal value; And
Extracting an approximate curve for the background value of the signal value from which the high-frequency component has been removed
/ RTI > 15. The method of claim 14,
The step of removing the background comprises:
Removing the high frequency component through a low pass filter; And
Extracting an approximate curve for the background value using a polynomial curve fitting;
/ RTI > 13. The method of claim 12,
The step of processing the normalization comprises:
Performing the normalization process on the signal value based on a ratio of an approximate curve equal to or greater than a normalization reference value and a difference value about an approximate curve equal to or less than the normalization reference value
/ RTI >

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