SE2030308A1 - Imaging material analyzer and procedure for using it - Google Patents

Abstract

Imaging material analyzer (114), intended for classifying and characterizing the material of surfaces (101), comprising at least one radiation emitting device (104,402) and at least one receiver (115). Radiation emitting device (104) emits light pulses, which are modulated by at least one modulator (106), against at least one surface (101) and that the reflected light from the surface (101) is detected by at least one camera (102) in the receiver (115). The camera (102) generates video signals (103) which are transmitted to at least one demodulator (109) which demodulates the generated video signals (103) and outputs digital signals (R1) to (RN) which are proportional to the intensity of the reflected light from the surface (101 ). The emitted light of the radiation emitting units (113) is controlled by sinusoidal pulse width modulated signals (105) modulated by the modulator (106), and the modulator (106) includes a synchronizing function which synchronizes the start time of the emitted pulses (105) and light pulses from the radiated emitting units. the start times of the camera's (102) exposures. The patent application also includes a method of using the material analyzer.

Description

Imaging material analyzer and method for using this Technical area The present invention relates to an imaging material analyzer, which is intended to be used for classification and characterization of surface materials in accordance with the patent claims, and a method for using this in accordance with the patent claims.

State of the art Techniques for classifying and characterizing materials by imaging spectral analysis of reflected electromagnetic radiation are already known. It is known, for example, that when a material is irradiated with electromagnetic radiation within the wavelength range covered by the present invention, the material's molecules and its cloud of electrons will oscillate due to the chemical binding energy between the molecules' atoms. This phenomenon can be approximated by a mechanical harmonic oscillation which in turn emits electromagnetic radiation, resulting in a scattered reflection of incoming radiation. At photon energies that match the molecules' corresponding resonance frequency or its harmonics, the molecule instead assumes a quantified higher energy level. This phenomenon therefore results in a strong absorption of electromagnetic radiation in the material for the wavelengths where the molecules exhibit resonance. In this way, the spectral distribution of the reflected radiation becomes a fingerprint of the analyzed material [1].

Via a scientific article by H. Jiang et.al [2] it is further known that a few characteristic wavelengths can be selected based on hyperspectral data using, among other things, principal component analysis. The aim is to be able to classify materials based on the reflection of light with only a few different wavelengths. The method can be used to select the wavelengths of the light emitters in an application-specific material analyzer. The application in this particular case is about detecting pressure damage on fruit.

In a similar way, Patrik Jonsson describes in a doctoral thesis from Mittuniversitetet [3] how a single camera, sensitive to light in the near-infrared wavelength range, can be used to classify road conditions: ice, snow, wet, dry asphalt. The system can provide guidance for better maintenance of winter roads. The technique is based on exposing a sequence of four images. For each of the four images, carefully selected optical bandpass filters are used which enable the use of Al where a subsequent classifier (KNN) identifies which areas within the camera's viewing area are covered with snow, water, ice or dry asphalt. The technique works well for viewing static areas, i.e. no movement in the image, this is due to the long time it takes to change filters and expose four images. The mechanical filter changer is an expensive solution, has a questionable function in cold and is slow. The described technology is an application-specific material analyzer, but for the reasons described only works for static surfaces.

Guterman et.al describe in a patent [4] a technique for imaging using unsynchronized amplitude modulated light. The fact that the modulated light is not synchronized with the camera means that the radiation of the light cannot be temporally concentrated to the periods when the image sensor exposes images. This in turn leads to a low signal-to-noise ratio (SNR) in the case of, for example, the influence of undesired strong sunlight. The technique is exemplified for video applications, although it could theoretically be applied to spectral material analysis.

Sten Löfving describes in a patent [5] a sensor for detecting road conditions. This sensor uses sigav modulated laser light but is not imaging, i.e. measures in a limited point. When the sensor is mounted on a vehicle, the measurement takes place at several points along the line that follows the vehicle's direction of travel. Described equipment is an application specific material analyzer but would need a scanning motion in two dimensions to become imaging.

T. Hyvärinen et.al from the Finnish company Specim describe in a scientific article [6] how a single imaging spectral camera with high spectral resolution was constructed. The basic technique is generally known under the name "push-broom", which means that optical components such as gratings or prisms are used to spread the light that has passed through a narrow slit opening. Along those of the dimensions of the two-dimensional detector, a line image is obtained, while the second dimension gives a spectral distribution of the light, dispersion. The technique only allows imaging of the line and not imaging in two dimensions like the technique Patrik Jonsson describes. However, if the object to be imaged has a linear movement in relation to the camera, 2 dimensions can be imaged as a sequence of lines. There is also a problem with light sensitivity which becomes very low for this technique as the captured light has to pass through a narrow slit-shaped opening. The cost of such a camera is usually high as the optical components needed to achieve the dispersion of the light are expensive. The equipment also often becomes large and heavy due to the optical components. In combination with, for example, halogen lighting, this camera can be used as a material analyzer.

Johan Casselgren et.al describes in a scientific article [7] a method for spectral imaging and classification of road conditions. There are problems with creating a controlled lighting environment outdoors with the help of active lighting. During the day there is a strong contribution of background light from the sun with very large variations. This article therefore describes a method for how the contribution from the active lighting can be separated from the background. Laser light is modulated binary, on or off, synchronously with image acquisition in such a way that a sequence of six images is exposed: background light, illumination with laser 1, background light, laser 2, background light and laser 3. Lasers 1, 2 and 3 emit light with different wavelengths. The method thus allows spectral coding of the light and that background light can be suppressed for static scenes but the disadvantage is that the slightest movement in the image will generate an incorrect result due to the time it takes to expose six times.

S. Bhattacharyya et.al describes in a scientific article [8] how a superheterodyne lock-in amplifier can be implemented digitally. The method is very effective for separating weak sinusoidal signals from other unwanted noise. By selecting different frequencies on the reference signal, signals with different frequencies can also be detected. This technique can therefore be advantageously used for spectral decoding of a sequence of images where active lighting with different wavelengths is modulated with different frequencies.

M. Lakka et.al describes in a scientific article [9] how a generator for sinusoidal pulse width modulated signals (SPWM) is used as a method to convert electrical energy from DC to AC voltage. Furthermore, it is described how the generator was implemented digitally on a circuit with programmable logic, FPGA.

There are problems with existing materials analysis techniques. Spectral cameras according to the "push-broom" technique can only image a line, they are large, heavy and expensive, have a low light sensitivity and lack the function to suppress the ambient light. The need to suppress the influence of the surrounding passive light becomes especially noticeable for those applications when the material analysis is done in an outdoor environment under the influence of strong and varying sunlight. Without suppression of the passive ambient light, the spectral distribution of the total light will vary over time, which in turn requires repetitive calibrations. To avoid these repeated calibrations, the total lighting environment should be dominated by the active lighting, which is significantly more stable over time. The existing techniques that use modulated light can certainly partially suppress ambient passive light but are in some cases bad at handling real-time characteristics, i.e. the motion imaging or they have built-in limitations in the ability to use radiated active lighting so that the SNR is maximized. Techniques where multiple exposures are used in combination with a mechanical filter changer become expensive, slow, and have questionable mechanical reliability. The purpose of the present invention is to eliminate or substantially reduce at least one of the previously mentioned, or in the following description, mentioned problems. The object is solved with a device and a method in accordance with the present patent application.

BRIEF DESCRIPTION OF FIGURES In the following detailed description of the present invention, reference and reference to figures will be made. Each figure is briefly described in the following list of figures. The figures are schematic and details may be omitted. The embodiments of the imaging material analyzer exemplified in the figures are therefore not limiting for the scope of protection of the present patent application. Figure 1 shows how overall components are connected to an imaging material analyzer.

Figure 2 shows a sinusoidal pulse width modulated signal used to control the emission of electromagnetic radiation. The image also shows how the pulses are synchronized with the image acquisition.

Figure 3 describes the main components and the calculations performed in the spectral demodulator. Figure 4 shows a preferred exemplary embodiment of the material analyzer. Figures 5 and 6 show alternative embodiments of the imaging material analyzer.

Figure 7 shows a procedure for selecting wavelengths Ål, equipping the radiation-emitting device with radiation-emitting units and configuring the modulator/demodulator. Figure 8 shows examples of three different situations for how the imaging material analyzer is used. Figure 9 shows a schematic exemplification of the temporal signal spectrum of the video signal.

Detailed description of the invention With reference to the figures and in accordance with the present patent application, a device named imaging material analyzer 114 is shown as well as a method for use and application adaptation of the imaging material analyzer 114. One or more surfaces 101 are assumed to consist of at least two different materials and/or at least one material with varying properties. The imaging material analyzer allows the materials that the surfaces are made of to be classified and characterized with non-contact measurement technology and where the imaging provides information on the distribution of the materials over the surfaces. The non-contact measurement technique means that the surfaces are irradiated with electromagnetic radiation and that the spectral distribution of the reflected radiation forms the basis for the classification and characterization of the materials. Typical areas of application for the invention are, for example: sorting of materials for recycling, characterization of raw materials such as, for example, moisture content in biomass or classification and characterization of crops over large areas. Distinctive for the imaging material analyzer is that it needs to be adapted and trained for the set of different materials it must sense again and/or characterize.

The most significant digit position in the numbered references always indicates the numbers 1 to 9 of the figures. The imaging material analyzer 114 consists of at least two main components: at least one radiation emitting device 104, and at least one receiver 115.

Figure 1 shows the two-dimensional surface 101 which is analyzed by a radiation emitting device 104, consisting of at least two or more radiation emitting units 113.1-113.N The figures show the radiation emitting units 113.1-113.N, which illuminate the surface 101. The N number of radiation emitting units emit electromagnetic radiation with wavelengths from a minimum of 100 nm to a maximum of Sum but where each individual radiation-emitting unit is characterized by maximum intensity at the wavelengths Ål to ÄN. In this patent application, where applicable, the word light can be used synonymously with electromagnetic radiation within a given wavelength range. Other wavelength ranges than 100 nm to 3 µm may occur in alternative embodiments. N and Å to Ä are parameters whose value is assigned in accordance with the procedure described in the present patent application. Where applicable, the remaining technical description and patent claims may refer to these parameters. The value of the parameter N indicates the number of radiation-emitting units and is at the same time controlling the dimensioning of modulator 106, demodulator 109 and AI unit 111. In the exemplary embodiment, the radiation-emitting units consist of LED lasers and/or LED diodes. An LED laser emits a near monochromatic, coherent light because a simpler LED emits light with a wider wavelength range than the LED laser. In alternative embodiments, flashing xenon lamps in combination with optical bandpass filters can be used. A single camera 102 images a surface 101 by recording the electromagnetic radiation that is reflected in the surface during repetitive time intervals called exposure time. The camera includes at least one image detector. These image detectors can be of the type one-dimensional for line imaging or two-dimensional for area imaging, whose pixels are sensitive to all existing wavelengths Ål to ÄN. The camera 102 generates at least one digital video signal 103 and at least one trigger signal 107 whose pulse signals the beginning of repetitive image exposures. Trigger signals are often present in digital designs where they are used to simultaneously "fire" events in more than one module, usually called synchronization. A modulator 106 generates N pieces of sinusoidal pulse width modulated signals 105 whose pulses determine when the N st. the radiation-emitting units 113.1-113.N must emit radiation.

Referring to Figure 2, an exemplary sinusoidal pulse width modulated signal is shown. Pulses 22 are started synchronously with the trigger signal 107, 21 that comes from the camera 102. The trigger signal therefore allows the pulses 22 to start simultaneously with the image exposure of the camera 102, but where the width of the pulses 24 is determined by the modulator 106. When the pulses 22 in the exemplified embodiment have a higher relative signal level than 80% emit corresponding radiation-emitting units 113.1-113.N electromagnetic radiation, which means that electromagnetic radiation radiates from the radiation-emitting units 113.1-113.N only during the times when the camera 102 exposes images. Other limit values than 80% for high signal level may occur in alternative embodiments. The repetition frequency of image exposures in the camera 102 is indicated by FC 27. The exposure time for the camera 102 should ideally be chosen to the maximum time during which any of the radiation emitting units 113.1-113.N emits electromagnetic radiation, i.e. maximum pulse width 24. The widths of the pulses 24 are modulated so that its width is in direct proportion to a time and amplitude discrete sinusoidal signal 23, commonly known as SPWM. The time- and amplitude-discrete values 25 therefore constitute a digital representation of the sinusoidal signal 23. N number of sinusoidal pulse-width modulated signals are thus generated in the modulator 106 with different frequencies fl to fN26 which may control the radiation-emitting units 113.1-113.N, characterized by the wavelengths Ål toÅN. The frequencies fl to fN are parameters whose value is assigned in accordance with the procedure described in the present patent application. Where applicable, the remaining technical description and patent claims may refer to these parameters. The digital signals 108 are proportional to the pulse widths 24 and thus represent the time and amplitude discrete sinusoidal signals Sl to SN and the corresponding cosine terms Cl to CN. The cosine terms have a single phase shift of 90 degrees relative to the sine wave 23 that controls the pulse widths 24. The digital signals 108 are used together with the video signal 103 in the spectral demodulator 109 to generate a series of digital signals Rl to RN proportional to the intensity of the electromagnetic radiation characterized by the wavelengths Eel to ÅN. The signals R1 to RN together constitute signatures for the materials of which the surface 101 consists.

The spectral demodulator is a digital implementation of a superheterodyne lock-in amplifier and is schematically depicted in Figure 3. The sine and cosine terms, 31 and 32 are multiplied by the video signal V 33 in digital multipliers 39. The resulting signals, 34 and 35 is then filtered in a bank of linear digital low-pass filters 36. These filters operate temporally, ie the filtering is only in the time domain for the respective pixel. The time domain of a pixel describes how the pixel's value changes over time for the sequence of images that make up the digital video signal. Finally, an arithmetical calculation 37 is made of the intensity of the reflected electromagnetic radiation Rl to RN, 38 for the respective wavelength Ål to ÅN. The fact that the sine and cosine terms, 31 and 32 have the same frequency fl 26 as for the corresponding emitted sinusoidal pulse width modulated electromagnetic radiation 22 with wavelength Ål means that the result of the arithmetic calculation 37 corresponds to the intensity of reflected electromagnetic radiation with the corresponding wavelength Ål.

In the exemplary embodiment, artificial intelligence is used which consists of at least one computer program in the AI unit 111. In its simplest form, the "K Nearest Neighbor" (KNN) algorithm is used for classification and characterization of the surface 101 constituent material. Examples of alternative artificial intelligence algorithms that may appear in alternative embodiments are neural networks or "Support Vector Machine" (SVM).

Figure 8 shows examples of three different situations where: the material analyzer 81 is mounted on a vehicle or autonomous vehicle 82 for analysis of surfaces 83 over large areas, the material analyzer 84 is mounted stationary over a conveyor belt 85 for continuous analysis of passing objects 86, the material analyzer 87 is used manually by a user 88 for analysis of selected object 89.

The present invention, an imaging material analyzer 114 needs to be adapted to the selected set of different materials that the user wishes to analyze. A prerequisite for the material analysis to be possible is that reflected electromagnetic radiation within the spectral wavelength range within which the receiver 115 is sensitive is also a carrier of information about the selected material. This information is usually concentrated to a few single wavelengths/wavelength ranges within the receiver's sensitivity range. Therefore, the following paragraphs describe a procedure for selecting these single wavelengths/wavelength ranges. Then the radiation emitting device is equipped in accordance with selected wavelengths/wavelength ranges and the modulator and demodulator are configured for the corresponding signal processing. Next, a procedure takes place where the material analyzer learns to classify selected materials and learns to characterize the properties of the materials. This learning is obtained by training an artificial intelligence unit 111.

Figure 7 is a flow graph of working steps that schematically compiles a procedure where the radiation emitting device 104 is equipped with a set of radiation emitting units 113.1-113.N and that modulator 106 and demodulator 109 are configured. The method means that the imaging material analyzer 114 is adapted for analysis of the limited set of different materials that the imaging material analyzer 114 must be able to analyze. Initially, a spectrograph, hyperspectral camera or similar instrument is needed to collect data 71 for the spectral distribution of the electromagnetic radiation reflected from surfaces of a limited set of different materials and where some of the materials may have varying properties. Principal component analysis 72 (a well-known statistical analysis method) is then performed on the collected data whereby projected data and projection coefficients are calculated. The coefficients then give good guidance as to which wavelengths/wavelength ranges are characterized by Å; 73 within the total analyzed spectral range that has the greatest importance for being able to classify and/or characterize the various materials included in the analysis. The data collected at 71 is then filtered with simulated optical filters 74 according to the choices made at 73. The result after filtering is a spectral description of the materials with considerably lower spectral resolution than that obtained with the spectrograph 71. Half of the filtered data is then used to train a classifier and/or pre-regression analysis of its properties, while the other half of the data is used for a simulated classification of materials and/or simulated characterization of the properties of the materials 75. Also other alternative distributions for splitting filtered data than half-half may occur.Was the classification or the characterization is substandard, the work steps 73, 74 and 75 must be repeated whereby other wavelengths Å; and possibly more radiation emitting units N are selected. If, however, the result of the classification and/or characterization is acceptable, the next step 76 is to equip the radiation emitting device 104 with a set of radiation emitting units 113.1-113.N characterized by the Å; previously selected at 73. Frequencies 26, f; for N the number of sinusoidal signals 108 must then be selected and the modulator configured accordingly. The demodulator 109 is configured for 2N the number of low-pass filters 36 and 2N signal paths for other calculations 39, 37. The configuration of the modulator and demodulator involves modification of source code for software and/or firmware, after which the imaging material analyzer 114 updated with new machine code and/or new programmable logic configuration files.

In figure 9, a schematic illustration of the temporal amplitude spectrum 91 of the video signal 103 is given. By temporal is meant an amplitude spectrum after analysis in the time domain of a single picture element (pixel). The triangular areas 92 constitute double bandwidth B for the video signal as a single radiation emitting unit 113.1-113.N cause. B is a parameter whose value is assigned according to the procedure described herein. Where applicable, the remaining technical description and patent claims may refer to the parameter B. B can be calculated according to formula 93, where N is the number of radiation-emitting units 113.1-113.N. FC 27, 97 is the repetition frequency for image exposures in the camera 102. The N frequencies f; which modulates the respective radiation emitting units 113.1-113.N can in the exemplary embodiment be selected according to formulas 95 and 96.Other selection of frequencies f; may occur in alternative embodiments. Equation 93 indicates a relationship between the repetition frequency of the image exposures FC 97, the number of radiation-emitting units N 113.1-113.N and the bandwidth B 92. Higher repetition frequency of image exposures FC 97 or fewer number of radiation-emitting units N 113.1-113.N allows greater bandwidth B 92. What determines the need for bandwidth B is the presence of motion in the image, faster motion requires greater bandwidth B for correct rendering. The bandwidth B is the same bandwidth that in the exemplary embodiment is suitably selected for the demodulator's 2N pieces of low-pass filter 36.

Alternative embodiments may have low-pass filter 36 with a different bandwidth than B.

The present patent application describes in detail a device and a method. The device is an imaging material analyzer 114 for classification and/or characterization of the materials that a surface consists of. Classification refers to decisions about which materials, based on a limited set of different materials, a surface consists of. The ability to classify materials based on spectral data is created through a previous training of artificial intelligence. Characterization refers to the calculation of one or more measurements that quantify a material's properties according to a mathematical relationship determined with regression analysis. Regression analysis refers to a statistical method for determining a mathematical relationship between spectral information and a surface property based on training data. Both classification and characterization are the results of calculations performed with an artificial intelligence unit called Al unit 111. Training and regression analysis are also the results of calculations performed with artificial intelligence but by executing software in a separate computer.

Analysis of materials takes place by the device 114 irradiating a surface with spectrally modulated electromagnetic radiation and at the same time quantifying reflected radiation. The device 114 demodulates quantified reflection which gives a spectral distribution of reflected radiation for each picture element (pixel). A method, schematically depicted in Figure 7, is used to adapt the device 114 to the limited set of different materials it must be able to classify and/or characterize, where the set of different materials is dependent on the application.

Exemplary embodiment In the following, a preferred embodiment of the present material analyzer is described where it is used to classify the various materials of which a two-dimensional surface 401 consists. Figure 4 shows the imaging material analyzer consisting of two main components: (1) a radiation emitting device 402, consisting of a group of radiation emitting units 413 and (2) a receiver 403. These two units are electrically connected via a cable 404, provided with a connector and which essentially transmits the signals T1 to TN, see 104 in Figure 1. This allows the analyzer to be equipped with an exchangeable radiation emitting unit 402, consisting of alternative groups of radiation emitting units 413. The radiation emitters characterized by the wavelengths Ål to ÄN which are chosen based on which materials need to be classified. Mechanically, components 402 and 403 are joined but detachable.

A pixelated image detector 406 with one or two dimensions images the surface 401. Imaging occurs by focusing light with a removable and replaceable lens 405 so that the image is projected onto the image detector 406. Algorithms and logic for 407 imaging, 408 spectral demodulator and modulator, 409 artificial intelligence, and 410 communication is in the exemplified embodiment implemented on a "field programmable logic array" (FPGA) in combination with microprocessors on one and the same integrated circuit. Wired or wireless communication 411 transfers recorded materials and properties to a personal computer, industrial computer or similar platform for measurement data collection 412.

Figure 5 shows an alternative embodiment where artificial intelligence 52 has been moved from the receiver unit 51 and instead implemented as software in the computer for measurement data collection 53.

Figure 6 shows another alternative embodiment where the imaging material analyzer has its own built-in graphic display 62 and can thus operate independently without connection to a computer 412. Graphics are generated in 61 for visualization of analysis results for a user 63.

Advantages of the invention With the present invention, a number of advantages are achieved. The most important one is that at least one of the stated problems in the background or description has been eliminated or reduced by known techniques.

The present invention modulates the active electromagnetic radiation with a sinusoidal, pulse width modulated (SPWM) waveform where the pulses are synchronized with the image exposure. This therefore means that the energy of the active electromagnetic radiation can be controlled to only the time intervals when the image exposure takes place. With modern LEDs or LED laser diodes, high light intensity can be created during very short pulses, which in turn allows extremely short exposure times and thus minimized contribution from ambient electromagnetic radiation. The sinusoidal variation of the pulse widths allows a varying light energy that appears as a sinusoidal intensity in a temporal sequence of pictures. The sinusoidally modulated intensity can then be effectively separated from the unmodulated ambient electromagnetic radiation by means of superheterodyne lock-in where the different wavelengths of the electromagnetic radiation are modulated with different frequencies 26. Suppression of ambient electromagnetic radiation therefore takes place in two steps: (1) by synchronized light pulses in combination with short image exposures , (2)by demodulation with superheterodyne lock-in. The first step protects the image detector from saturation, for example in the case of strong electromagnetic radiation from the sun. It is extremely important to include a means of protecting the image detector from saturation because no known demodulation technique can otherwise suppress the ambient electromagnetic radiation.

During the demodulation, the intensity of the reflected electromagnetic radiation is calculated for the respective radiation-emitting unit. This demodulation takes place on the basis of the same temporal set of image data for all spectral channels and not different sets as in the case of time-multiplexed modulation described by Johan Casselgren et.al. Therefore, the present invention has excellent real-time properties and gives good results even where motion is present in the image while simultaneously suppressing the surrounding passive electromagnetic radiation in two stages in an extremely efficient manner. No other known technique for imaging material analysis has succeeded in combining these important properties.

The present invention modulates electromagnetic radiation with different wavelengths instead of using optical components for dispersion or mechanical solutions for filter replacement.

The material analyzer is thus cheaper, smaller and lighter than competing technologies.

In the detailed description of the present device and method, details may be omitted that are obvious to a person skilled in the art in the field in which the device and method are included. Such obvious details are included to the extent necessary for the proper functioning of the present device and method to be obtained . Although certain preferred embodiments of the device and the method have been described in more detail, variations and modifications of the device and the method may become apparent to those skilled in the art in the field of the invention. All such modifications and variations are considered to fall within the scope of the subsequent patent claims. 12 References [1][2] [3] [4] [5] [6] [7] [8] [9] B. Stuart, Bio/ogical applications of infrared spectroscopy, Wiley, 1997 H. Jiang et.a |, "Wavelength Selection for Detection of Slight Bruises on Pears Based on Hyperspectral|maging", Applied Sciences, v. 6, no. 12, pp. 450, I\/|DP| 2016 P. Jonsson, Surface Status Classification, Uti/izing Image Sensor Technology and Computer Models, Doctoral thesis no. 219, Mid Sweden University, 2015.

Guterman et.al., "Methods of producing video images that are independent of the background lighting", US Patent no. US 10,630,907. B2, 21st of April 2020.

Sten Löfving, "Optical method to estimate properties of an ice- or water-covered measuring object", Swedish patent, number SE 531 949 C2, September 15, 2009.

T. Hyvärinen et.a|, "Compact high-resolution VIS/NIR hyperspectral sensor", Proceedings of the SPIE -The International Society for Optical Engineering, v. 8032, Conference: Next-Generation SpectroscopicTechnologies IV, 25-26 April 2011, Orlando, FL, USA.

J. Casselgren et.a|, "Road condition analysis using NIR illumination and compensating for surrounding light", Optics and Lasers in Engineering, v 77, pp. 175-82, Feb. 2016 S. Bhattacharyya et.a|, "Implementation of Digital Lock-in Amplifier", Journal of Physics: ConferenceSeries, v 759, 2016 l\l|.Lakka et.a|, "Development of an FPGA-Based SPWM Generator for High Switching Frequency DC/AC |nverters", IEEE Transactions on Power Electronics, v.29, no. 1, January 2014

Claims (3)

1. Imaging material analyzer (114), intended to be used for classification and characterization of materials in at least one surface (101), which includes at least one radiation-emitting device (104,402) and at least one receiver (115), which radiation-emitting device (104) emits pulses of electromagnetic radiation with maximum intensity at the wavelengths (A1 to ÄN), which is modulated by at least one modulator (106), towards at least one surface (101) and that the reflected electromagnetic radiation from the surface (101) is recorded by at least one camera (102) in the receiver (115) ,which camera (102) generates video signals (103) which are transmitted to at least one end modulator (109) which demodulates the generated video signals (103) and emits digital signals (R1) to (RN) and that the radiation emitting device (104) comprises at least a first radiation emitter unit (113.1) which emits modulated electromagnetic radiation with a maximum intensity at a first wavelength (A1) and at least one second radiation emitting unit (113.2) which emits modulated electromagnetic radiation with a maximum intensity at a second path length (A2), characterized in that the radiation emitting units (113.1-113.N) emitted electromagnetic radiation is controlled by pulses (105) modulated into sinusoidal, pulse width modulated waveforms by the modulator (106), and that the modulator (106) includes a synchronization function that synchronizes the start time of the emitted pulses (105) and the pulses of electromagnetic radiation from the radiation emitting units with the starting times of the camera (102) exposures, and that the digital signals (R1) to (RN) are proportional to the intensity of the light reflected in the surface (101) and emitted from the respective radiation emitting units (113.1-113.N ) with maximum radiated intensity at the corresponding wavelengths (Ål) to (ÄN). 2. Imaging material analyzer (114) in accordance with claim 1 characterized in that the radiation emitting units (11 3.1-113.N) emit electromagnetic radiation with wavelengths in the range 100 nm to 3 pm. Imaging material analyzer (114) in accordance with one of patent claims 1 or 2, characterized in that the radiation-emitting units (113.1-113.N) consist of LED lasers. Imaging material analyzer (114) in accordance with one of patent claims 1 to 2, characterized in that the radiation-emitting units (113.1-113.N) consist of LEDs. Imaging material analyzer (114) in accordance with one of claims 1 to 2, characterized in that the radiation emitting units (113.1-113.N) consist of a combination of LED lasers and LED diodes. Imaging material analyzer (114) according to one of the preceding claims 1 to 4, characterized in that the spectral demodulator (109) is a digital implementation of a superheterodyne lock-in amplifier. Imaging material analyzer (114) in accordance with at least one of the previous patent claims characterized in that the imaging material analyzer comprises at least one Al unit (111) Imaging material analyzer (114) in accordance with patent claim 7 characterized in that the Al unit (111) comprising at least one computer program comprising at least one algorithm, with which the constituent materials of the surface (101) are classified and a characterization of one or more measurements regarding properties of the constituent materials of the surface (101) is performed. Imaging material analyzer (114) in accordance with patent claim 1 characterized in that the camera (102) comprises at least one one-dimensional and/or at least one two-dimensional image detector whose pixels are sensitive to all existing wavelengths Ål to ÄN Imaging material analyzer (114) in accordance with patent claim 1 characterized in that the the radiation emitting units (113.1-113.N) are replaceable and/or that the radiation emitting device (104) is replaceable. Imaging material analyzer (114) in accordance with patent claim 1 characterized in that the radiation emitting device (104) and the receiver (115) are made up of separate units. Imaging material analyzer (114) in accordance with patent claim 1 characterized in that the radiation emitting device (104) and the receiver (115) are integrated in one unit. Imaging material analyzer (114) in accordance with at least one of the preceding claims, characterized in that the imaging analyzer comprises a bank of linear digital low-pass filters (36) operating temporally, that is, filtering the time domain of each pixel data. Imaging material analyzer (114) in accordance with at least one of the previous patent claims, characterized in that it includes at least one graphics generator. Method for using the imaging material analyzer (114) in accordance with at least one of the patent claims 1 to 14, characterized in that the radiation-emitting device (104) is equipped with a required N number of radiation-emitting units (113.1-113.N), with maximum intensity at the wavelengths (Ål to ÄN), selected to enable the classification of materials in the surface (101) and/or to enable the characterization of the properties of the materials included in the surface (101), after which the modulator (106) and the demodulator (109) are configured according to the selected set of radiation emitting units ( 113.1-113.N), that the modulator (106) emits N number of sinusoidal pulse width modulated signals (105, 22) whose pulses 22 control the emitted electromagnetic radiation of the radiation-emitting units (113.1-113.N) towards the surface (101), 16. 17. 18. that the camera (102) emits a trigger signal (107, 21) at each exposure to the modulator (106) which synchronizes the start time of the respective pulse (22) with the start time of the camera's (102) exposure, that the camera (102) registers the reflected electromagnetic the radiation and generates at least one digital video signal (103) which digital video signal (103) is demodulated in the demodulator (109) and that the demodulator (109) emits N number of digital signals (R1) to (RN) which are proportional to the intensity at the corresponding N number of wavelengths (Ål to ÄN) of the reflected electromagnetic radiation from the surface (101), that the digital signals (R1) to (RN) are the basis for a classification of the surface's constituent materials and a characterization of the materials' properties. Method for using the imaging material analyzer (114) in accordance with patent claim 15 characterized in that the sinusoidal pulse width modulated signals (105, 22) generated in the modulator (106) are generated with N number of different frequencies f1' to fN. Method for using imaging material analyzer (114) in accordance with patent claim 16 characterized in that the N number of different frequencies f1 to fN calculated according to formula (94) according to below fi= 2iB where the variable i is defined according to formula (95) according to below i = 1 .. .N and that the bandwidth is defined according to the formula (93) as below B=Fc/4(N+1) Method for using imaging material analyzer (114) in accordance with one of the patent claims 15 to 17 characterized in that when those of the modulator (106) the emitted pulses (105, 22) have a higher relative signal level than 80%, the corresponding radiation-emitting units (113.1-113.N) emit electromagnetic radiation, which means that electromagnetic radiation is emitted from the radiation-emitting units (113.1-113.N), only during the times as the camera 102 exposes images. Method for using the imaging material analyzer (114) in accordance with any of the patent claims 15 to 18 characterized in that the exposure time of the camera (102) is ideally selected to the time corresponding to the maximum pulse width (24), during which any of the radiation emitting units (113.1-113. N) emits electromagnetic radiation. Method for using an imaging material analyzer (114) in accordance with at least one of patent claims 15 to 19, characterized in that the adaptation of the imaging material analyzer includes equipping the radiation emitting device (104) with N number of radiation emitting units (113.1-113.N), where the number is N radiation-emitting units (113.1-113.N), as well as the selection of the radiation-emitting units' (113.1-113.N) wavelengths (Ål to ÄN), takes place with a one-part procedure where spectral data is collected for the materials to be classified with the imaging material analyzer with at least one spectrograph, alternatively at least one hyperspectral camera or the like, after which a principal component analysis of the collected spectral data (the data set) is carried out so that projected data and the coefficients of the projection are calculated, which coefficients give guidance on which wavelengths/wavelength ranges characterized by Å; within the total analyzed spectral range which has the greatest significance for the classification of the various materials. Method for using the imaging material analyzer (114) in accordance with patent claim 20, characterized in that the collected spectral data set is filtered with simulated optical filters according to the choices that the coefficients entailed, resulting in a spectral description of the materials with a significantly lower spectral resolution than that obtained with the spectrograph being obtained, after which half of the filtered dataset is used to train a classifier, while the other half of the data is used for a simulated classification of the materials. Method for using the imaging material analyzer (114) in accordance with patent claim 21 characterized in that if the classification turned out to be substandard, the working steps (73, 74, 75) must be repeated, the result of the classification was acceptable, the next step is to equip the radiation emitting device (104) with a set N radiation emitting devices (113.1-113.N) which are characterized by the Å;previously selected data which is filtered with simulated optical filters wavelength characteristics of radiation emitting devices, after which a classification/simulation takes place with artificial intelligence until an approved result is achieved, after which the radiation emitting device is equipped and that the modulator and the demodulator is configured. Method for using the imaging material analyzer (114) in accordance with at least one of the patent claims 15 to 22 characterized in that the configuration of the modulator (106) and demodulator (109) respectively takes place by modifying the source code for software and/or firmware, after which the imaging material analyzer 114 is updated with new machine code and/or new programmable logic configuration files. Method for using the imaging material analyzer (114) in accordance with at least one of the patent claims 15 to 24 characterized in that during the demodulation of the digital signals (103) with the demodulator (109) the sine and cosine terms, (31) and (32) are multiplied with the video signal V (33) in digital multipliers (39) to the resulting signals, (34) and (35) which are then filtered in a bank of linear digital low-pass filters (36) whose passband has a width chosen to B, which filter operate temporally, i.e. filtered in the time domain for the respective pixel data after which an arithmetical calculation (37) of the intensity of the reflected electromagnetic radiation R1 to RN, (38) for the respective wavelength (Ål to ÄN ) is performed. Use of the imaging material analyzer (114) in a vehicle or an autonomous vehicle. Use of the imaging material analyzer (114) stationary application. Using the imaging material analyzer (114) manually.