CN110708524A - Target projection indicating device based on spectral imaging - Google Patents

Target projection indicating device based on spectral imaging Download PDF

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Publication number
CN110708524A
CN110708524A CN201910336082.XA CN201910336082A CN110708524A CN 110708524 A CN110708524 A CN 110708524A CN 201910336082 A CN201910336082 A CN 201910336082A CN 110708524 A CN110708524 A CN 110708524A
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image
target
value
spectral
pixel
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黄威
钟燕飞
张洪艳
李志刚
许小京
王桂强
张良培
罗旭东
张洋
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GUANGZHOU XINGBO SCIENTIFIC INSTRUMENTS CO Ltd
Wuhan University WHU
Institute of Forensic Science Ministry of Public Security PRC
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GUANGZHOU XINGBO SCIENTIFIC INSTRUMENTS CO Ltd
Wuhan University WHU
Institute of Forensic Science Ministry of Public Security PRC
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3141—Constructional details thereof
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H04N9/3185—Geometric adjustment, e.g. keystone or convergence

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Abstract

The invention discloses a target projection indicating device, which comprises a camera module, an image information processing and analyzing module and a projector module, wherein the camera module is used for shooting a target; the camera module is used for shooting an image of an area where a target is located; the image information processing and analyzing module is used for analyzing and processing the image information shot by the camera module to extract the position of the target, generating an image with a target position indication mark, and projecting the image with the target position indication mark to the area where the target is located through the projector module, so that the indication of the position where the target is located is realized, and convenience is provided for case handling personnel.

Description

Target projection indicating device based on spectral imaging
Technical Field
The invention relates to a spectral imaging technology, in particular to a target projection indicating device based on spectral imaging.
Background
At present, the spectrum imaging is widely applied to searching fingerprints and spots on site, and particularly, the spectrum imaging with different wavelengths can find some fingerprints and spots which cannot be seen by naked eyes originally and are hidden under a complex background, so that the spectrum imaging is widely popular and applied to office workers and other office staff.
After the target image is extracted by spectral imaging and software analysis, how to find the target position extracted by the software is also a difficult problem. Since the target is not easy to find by naked eyes, if the position of the target can be indicated by technical means, great convenience is provided for case handling personnel.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a target projection indicating device to indicate the position of a site target and provide convenience for acquiring the target.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a target projection indicating device comprises a camera module, an image information processing and analyzing module and a projector module; wherein the content of the first and second substances,
the camera module is used for shooting an image of an area where a target is located;
the image information processing and analyzing module is used for analyzing and processing the image information shot by the camera module to extract the position of the target, generating an image with a target position indication mark, and projecting the image with the target position indication mark to the area where the target is located through the projector module to realize the indication of the position where the target is located.
The projector module employs a single or two or three light sources.
The camera module is a spectral imaging camera.
The projector module adopts a DLP projector or a LCOS projector or an LCD projector or a projector of a laser beam scanning mode
The image information processing and analyzing module analyzes and extracts the position of the target by the following steps:
step one, salt and pepper-like noise suppression
Denoising image information shot by a camera module by adopting a space and spectrum domain adaptive median filter method to obtain a hyperspectral imaging image; x is an image matrix with m rows, n columns and L wave bands;
secondly, acquiring end member spectrum set of each target component of the target image
Automatically extracting all end members of the denoised hyperspectral imaging image by adopting a method of monosome volume growth analysis;
thirdly, performing spectral decomposition on the imaging spectral image on the basis of the extracted pure spectrum
According to each end member in all the extracted end member decomposition images, the decomposition calculation is restricted by two constraints, wherein the contribution of each obtained target component is not negative, and the sum of the contributions of each target component is 1.
The first step is specifically as follows:
let the spectral values at point (x, y) in the L-th band be f (i, j, L), GwIs the spectral operating window, lambda, of the current operating spectral domainmin、λmaxAnd λmedRespectively is the spectral minimum value, the spectral maximum value and the spectral median value G of each pixel element in the current spectral windowmaxIs a preset allowable maximum spectrum window; and is provided with SwFor the size of the current spatial filter window, fmin、fmaxAnd fmedRespectively the minimum value, the maximum value and the median value, S, in the current wave band space domain windowmaxA maximum window of a preset allowable spatial domain; the spectral value is the gray value of an image pixel point, the spectral window is a certain spectral range, and the spatial domain window is a certain pixel point region;
step 101: if λmin＜λmed＜λmaxThen go to step 102; otherwise G is increasedwIf G is increasedwIs less than GmaxThen, repeat step 101;
step 102: if λmin＜f(i,j,l)＜λmaxIf so, f (i, j, l) is output, otherwise, λ is outputmed；
Step 103: replacing the pixel value f (i, j, l) processed currently by the output value processed in steps 101 and 102 to be f (i, j)med；
Step 104: when f ismin＜fmed＜fmaxGo to step 105; otherwise, the spatial domain window S is increasedwIf the increased size is smaller than SmaxThen step 104 is repeated;
step 105: if fmin＜f(i,j)med＜fmaxThen output f (i, j)medOtherwise output fmed；
Wherein, the value output in step 105 is used as the value of the current band of the current pixel after denoising, and each pixel executes the steps 101 to 105 one by one to realize image denoising and obtain imaging spectrum data
Figure BDA0002039177950000021
Is an L row m x n column matrix transformed by an image matrix having m rows, n columns and L bands.
In step two, the method for analyzing the increase of the volume of the monomorphic body comprises the following specific steps:
step 201: denoising imaging spectrum data
Figure BDA0002039177950000022
Performing principal component conversion
Assuming that p is the total number of end members to be extracted, converting the image into a principal component characteristic image by using principal component conversion, and reserving characteristic images corresponding to the previous p-1 maximum characteristic values
Figure BDA0002039177950000031
Step 202: determining the first end member
Randomly selecting a pixel at any position in the first main component image corresponding to the maximum characteristic value, recording the value of the pixel as t, traversing each pixel of the image, and recording the value of a certain pixel as y without loss of generality1,iCalculating
Figure BDA0002039177950000032
All the traversed pixels are calculated; marking Q as a coordinate set corresponding to the end member spectrum, marking a pixel corresponding to the maximum value in all calculation results as a first end member, and adding the corresponding coordinate into the set Q;
step 203: the k (k is more than 1 and less than or equal to p) end members are extracted, and the k-1 extracted end members are recorded in
Figure BDA0002039177950000033
The end member value of the corresponding position of the first k-1 characteristic images is
Figure BDA0002039177950000034
Traversing each pixel of the image, keeping the value of a certain pixel as x without loss of generalityp-1,iIs provided with
Figure BDA0002039177950000035
Computing
Figure BDA0002039177950000036
1, taking k as a row vector, performing calculation on all traversed pixels, marking the pixel corresponding to the maximum value in all calculation results as the kth end member, and adding the corresponding coordinate of the kth end member into a set Q; when k is<p, continuously repeating the step;
step 204: from the imageExtracting the pixels corresponding to all coordinates of the set Q to obtain the final end member spectrum
Figure BDA0002039177950000038
The third step is specifically as follows:
hypothetical image
Figure BDA0002039177950000039
The spectrum of any pixel is an L-dimensional column vector x, the contribution information of each target component to be solved is represented by a p-dimensional vector a, and then:
Figure BDA00020391779500000310
s.t.1Ta＝1,0≤a≤1
wherein, s.t.1Ta is 1, a is more than or equal to 0 and less than or equal to 1, and 0 is [0,0]T，1＝[1,1,...,1]T。
Compared with the prior art, the invention has the beneficial effects that:
the invention captures the image of the area where the material evidence target is located through the camera module, the image information processing and analyzing module analyzes and processes the image information captured by the camera module to extract the position of the target, an image with a target position indication mark is generated according to the extracted target position, and then the image with the position indication mark is projected to the area where the target is located through the projector module, thereby realizing the indication of the position where the material evidence target is located.
Drawings
Fig. 1 is a schematic diagram illustrating an operating principle of a target projection indicating device according to an embodiment of the present invention;
FIG. 2 is a block diagram of a target projection pointing device according to an embodiment of the present invention;
FIG. 3 is an original image captured by the camera module;
FIG. 4 is an image of a target location indicator projected by a projector module;
FIG. 5 is a schematic diagram of an LED light source DLP projector;
FIG. 6 is a schematic diagram of the operation of the DMD chip;
in the figure: 1. a camera module; 2. an image information processing and analyzing module; 3. a projector module.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and detailed description.
Example (b):
referring to fig. 1-2, the spectral imaging indicating device provided in the present embodiment includes a camera module 1, an image information processing and analyzing module 2, and a projector module 3. In the present embodiment, the camera module 1 is a spectral imaging camera, but in other embodiments, the camera module 1 is not limited to a spectral imaging camera.
The camera module 1 is configured to capture an image of an area where a physical evidence target is located, as shown in fig. 3; the image information processing and analyzing module 2 is configured to analyze and process image information captured by the camera module 1, acquire physical evidence information, extract a position of a physical evidence target, generate an image with a target position indication identifier, and project the image with the target position indication identifier to an area where the target is located through the projector module 3, so as to achieve indication of the position where the target is located. As shown in fig. 4, after being projected by the projector module 3, a red arrow is projected in the area where the physical evidence target is located to indicate the position of the physical evidence, so as to indicate the direction for the field personnel to find the target.
Specifically, in the present embodiment, the projector module 3 is a DLP projector, which generates a digital image by using a DMD chip and projects a pattern through a projection lens. The projection light source can be an LED light source or a laser light source, the color is pure, and the semiconductor light source is convenient to use. Fig. 5 shows a schematic diagram of a DLP projector, which is composed of a light source, a light condensing and uniformizing system, a DMD chip and a projection lens. Of course, in other embodiments, the projector module 3 may employ other projectors, such as LCOS, LCD, or laser beam scanning.
Fig. 6 is a schematic diagram of the operation of the DLP display chip DMD. The deflection of the micro-mirror ON the DMD reflects light into the projector lens as ON, and the deflection of the micro-mirror reflects light to other locations and is absorbed as OFF.
In the present embodiment, the specifications of the projector module 3 are formulated as follows:
single-chip DLP projector
DMD: 0.33 inch 1080p chip
Brightness: 1000 lumen
Contrast ratio: 1000:1
Uniformity: more than 80 percent
An illumination light source: semiconductor, LED or laser
Since the projector module 3 is only used for projecting position markers, a single or two or three light sources, such as a single red (or green/blue) light source, can be used, which can reduce power consumption, weight and cost.
Meanwhile, the projector module 3 and the spectral imager 1 can be mechanically fused to ensure that the two form a whole, so that field personnel can operate conveniently and guide clearly.
The first problem encountered in the process of applying the imaging spectral image analyte evidence is that different target components in the image need to be separated, in this embodiment, first, a pure spectrum represented by each target is extracted, and then, based on the consideration of a mixed spectrum, the imaging spectral image is subjected to spectral decomposition based on the extracted pure spectrum, so as to accurately separate the different target components in the image, and specifically, the image information processing and analyzing module analyzes and extracts the positions of the targets through the following steps:
step one, salt and pepper-like noise suppression
Denoising image information shot by a camera module by adopting a space and spectrum domain adaptive median filter method to obtain a hyperspectral imaging image; x is an image matrix with m rows, n columns and L bands. The method specifically comprises the following steps:
the space-spectrum domain self-adaptive median filtering is to change the size of a filtering window according to the noise density, and simultaneously adopt different processing methods for noise points and signal points, namely, to carry out median filtering on the noise points, and the signal points keep the original spectrum value unchanged. Let the spectral values at point (x, y) in the L-th band be f (i, j, L), GwIs the spectral operating window, lambda, of the current operating spectral domainmin、λmaxAnd λmedRespectively the actual spectral minimum value, spectral maximum value and spectral median, G, of each pixel element in the current spectral windowmaxIs a preset allowable maximum spectrum window; and is provided with SwFor the size of the current spatial filter window, fmin、fmaxAnd fmedRespectively the minimum value, the maximum value and the median value, S, in the current wave band space domain windowmaxA maximum window of a preset allowable spatial domain; the spectral value is the gray value of an image pixel point, the spectral window is a certain spectral range, and the spatial domain window is a certain pixel point region;
step 101: if λmin＜λmed＜λmaxThen go to step 102; otherwise G is increasedwIf G is increasedwIs less than GmaxThen, repeat step 101; by increasing G stepwisewFirstly, the calculation amount can be reduced, and the deviation can be reduced.
Step 102: if λmin＜f(i,j,l)＜λmaxIf so, f (i, j, l) is output, otherwise, λ is outputmed；
Step 103: replacing the pixel value f (i, j, l) processed currently by the output value processed in steps 101 and 102 to be f (i, j)medThat is, f (i, j)medIs the result obtained after integrating steps 101 and 102.
Step 104: when f ismin＜fmed＜fmaxGo to step 105; otherwise, the spatial domain window S is increasedwIf the increased size is smaller than SmaxThen step 104 is repeated;
step 105: if fmin＜f(i,j)med＜fmaxThen output f (i, j)medOtherwise output fmed；
Wherein, the value output in step 105 is used as the value of the current band of the current pixel after denoising, and each pixel executes the steps 101 to 105 one by one to realize image denoising and obtain imaging spectrum data
Figure BDA0002039177950000061
Is an L row m x n column matrix transformed by an image matrix having m rows, n columns and L bands.
Secondly, acquiring end member spectrum sets of target components of the material evidence image
Step 201: denoising imaging spectrum dataPrincipal component transformation to reduce dimensionality of hyperspectral image data
Assuming that p is the total number of end members to be extracted, converting the image into a principal component characteristic image by using principal component conversion, and reserving characteristic images corresponding to the previous p-1 maximum characteristic values
Figure BDA0002039177950000063
Is a characteristic wave band image set corresponding to p-1 characteristic values.
Step 202: determining the first end member
Randomly selecting a pixel at any position in the first main component image corresponding to the maximum characteristic value, recording the value of the pixel as t, traversing each pixel of the image, and recording the value of a certain pixel as y without loss of generality1,iPerforming determinant calculation
Figure BDA0002039177950000064
All the traversed pixels are calculated; marking Q as a coordinate set corresponding to the end member spectrum, marking a pixel corresponding to the maximum value in all calculation results as a first end member, and adding the corresponding coordinate into the set Q;
step 203: the k (k is more than 1 and less than or equal to p) end members are extracted, and the k-1 extracted end members are recorded in
Figure BDA0002039177950000065
The end member value of the corresponding position of the first k-1 characteristic images is
Figure BDA0002039177950000071
Traversing each pixel of the image, keeping the value of a certain pixel as x without loss of generalityp-1,iIs provided with
Figure BDA0002039177950000072
Computing
Figure BDA0002039177950000073
1, taking k as a row vector, performing calculation on all traversed pixels, marking the pixel corresponding to the maximum value in all calculation results as the kth end member, and adding the corresponding coordinate of the kth end member into a set Q; when k is<p, continuously repeating the step;
Figure BDA0002039177950000074
a new wave band image set generated when the end member is extracted;
step 204: from the image
Figure BDA0002039177950000075
Extracting the pixels corresponding to all coordinates of the set Q to obtain the final end member spectrum
Figure BDA0002039177950000076
Thirdly, performing spectral decomposition on the imaging spectral image on the basis of the extracted pure spectrum
Hypothetical image
Figure BDA0002039177950000077
The spectrum of any pixel is an L-dimensional column vector x, the contribution information of each target component to be solved is represented by a p-dimensional vector a, and then:
Figure BDA0002039177950000078
s.t.1Ta＝1,0≤a≤1
wherein, s.t.1Ta is 1, a is more than or equal to 0 and less than or equal to 1, and 0 is [0,0]T，1＝[1,1,...,1]TThe problems are calculated by adopting a quadratic programming algorithm based on an active set.
The above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention accordingly, and not to limit the protection scope of the present invention accordingly. All equivalent changes or modifications made in accordance with the spirit of the present disclosure are intended to be covered by the scope of the present disclosure.

Claims (9)

1. A target projection indicating device is characterized by comprising a camera module, an image information processing and analyzing module and a projector module; wherein the content of the first and second substances,
the camera module is used for shooting an image of an area where a target is located;
the image information processing and analyzing module is used for analyzing and processing the image information shot by the camera module to extract the position of the target, generating an image with a target position indication mark, and projecting the image with the target position indication mark to the area where the target is located through the projector module to realize the indication of the position where the target is located.
2. The object projection pointing device of claim 1, wherein the projector module employs a single or two or three light sources.
3. The object projection pointing device of claim 1 or 2, wherein the camera module and the projector module are mounted integrally.
4. The object projection pointing device of claim 3, wherein the camera module is a spectral imaging camera.
5. The object projection indicating device of claim 3, wherein the projector module is a DLP projector or a LCOS projector or an LCD projector or a laser beam scanning type projector.
6. The object projection pointing device according to claim 4, wherein the image information processing and analyzing module analyzes and extracts the position of the object by:
step one, salt and pepper-like noise suppression
Denoising image information shot by a camera module by adopting a space and spectrum domain adaptive median filter method to obtain a hyperspectral imaging image; x is an image matrix with m rows, n columns and L wave bands;
secondly, acquiring end member spectrum set of each target component of the target image
Automatically extracting all end members of the denoised hyperspectral imaging image by adopting a method of monosome volume growth analysis;
thirdly, performing spectral decomposition on the imaging spectral image on the basis of the extracted pure spectrum
According to each end member in all the extracted end member decomposition images, the decomposition calculation is restricted by two constraints, wherein the contribution of each obtained target component is not negative, and the sum of the contributions of each target component is 1.
7. The object projection pointing device of claim 6, wherein the first step is specifically:
let the spectral values at point (x, y) in the L-th band be f (i, j, L), GwSpectral operating window for current operating spectral domainA mouth, lambdamin、λmaxAnd λmedRespectively is the spectral minimum value, the spectral maximum value and the spectral median value G of each pixel element in the current spectral windowmaxIs a preset allowable maximum spectrum window; and is provided with SwFor the size of the current spatial filter window, fmin、fmaxAnd fmedRespectively the minimum value, the maximum value and the median value, S, in the current wave band space domain windowmaxA maximum window of a preset allowable spatial domain; the spectral value is the gray value of an image pixel point, the spectral window is a certain spectral range, and the spatial domain window is a certain pixel point region;
step 101: if λmin＜λmed＜λmaxThen go to step 102; otherwise G is increasedwIf G is increasedwIs less than GmaxThen, repeat step 101;
step 102: if λmin＜f(i,j,l)＜λmaxIf so, f (i, j, l) is output, otherwise, λ is outputmed；
Step 103: replacing the pixel value f (i, j, l) processed currently by the output value processed in steps 101 and 102 to be f (i, j)med；
Step 104: when f ismin＜fmed＜fmaxGo to step 105; otherwise, the spatial domain window S is increasedwIf the increased size is smaller than SmaxThen step 104 is repeated;
step 105: if fmin＜f(i,j)med＜fmaxThen output f (i, j)medOtherwise output fmed；
Wherein, the value output in step 105 is used as the value of the current band of the current pixel after denoising, and each pixel executes the steps 101 to 105 one by one to realize image denoising and obtain imaging spectrum data
Figure FDA0002039177940000021
Figure FDA0002039177940000022
Is aAn L row m x n column matrix transformed by an image matrix having m rows and n columns and L bands.
8. The projection target pointing device according to claim 6 or 7, wherein in step two, the method using the volumetric growth analysis of the simple volume comprises the following specific steps:
step 201: denoising imaging spectrum data
Figure FDA0002039177940000023
Performing principal component conversion
Assuming that p is the total number of end members to be extracted, converting the image into a principal component characteristic image by using principal component conversion, and reserving characteristic images corresponding to the previous p-1 maximum characteristic values
Figure FDA0002039177940000024
Step 202: determining the first end member
Randomly selecting a pixel at any position in the first main component image corresponding to the maximum characteristic value, recording the value of the pixel as t, traversing each pixel of the image, and recording the value of a certain pixel as y without loss of generality1,iCalculating
Figure FDA0002039177940000025
All the traversed pixels are calculated; marking Q as a coordinate set corresponding to the end member spectrum, marking a pixel corresponding to the maximum value in all calculation results as a first end member, and adding the corresponding coordinate into the set Q;
step 203: the k (k is more than 1 and less than or equal to p) end members are extracted, and the k-1 extracted end members are recorded in
Figure FDA0002039177940000031
The end member value of the corresponding position of the first k-1 characteristic images is
Figure FDA0002039177940000032
Traversal graphEvery pixel of the image, without loss of generality, takes a certain pixel value as xp-1,iIs provided with
Figure FDA0002039177940000033
Computing
Figure FDA0002039177940000034
1, taking k as a row vector, performing calculation on all traversed pixels, marking the pixel corresponding to the maximum value in all calculation results as the kth end member, and adding the corresponding coordinate of the kth end member into a set Q; when k is<p, continuously repeating the step;
step 204: from the image
Figure FDA0002039177940000035
Extracting the pixels corresponding to all coordinates of the set Q to obtain the final end member spectrum
Figure FDA0002039177940000036
9. The target projection pointing device of claim 6, wherein the step three is specifically:
hypothetical image
Figure FDA0002039177940000037
The spectrum of any pixel is an L-dimensional column vector x, the contribution information of each target component to be solved is represented by a p-dimensional vector a, and then:
Figure FDA0002039177940000038
s.t.1Ta＝1,0≤a≤1
wherein, s.t.1Ta is 1, a is more than or equal to 0 and less than or equal to 1, and 0 is [0,0]T，1＝[1,1,...,1]T。
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