TW202135730A - SYSTEM AND METHOD FOR ANALYZING GAIT FOOTPRINTS BASED ON α-TYPE MULTISPECTRAL IMAGES - Google Patents

Abstract

A multi-spectral imaging system that captures gait and footprint analysis on a non-transparent artificial walkway includes using a multi-spectral thermal imager to be placed above and/or under the walkway, for example, when there are elderly people walking or standing on this walkway, then the gait behavior and footprint information can be instantly captured by the multi-spectral thermal imager, including far-infrared thermal images with a wavelength range of 8-14um, near-infrared images with a wavelength range of 0.94um, and with a wavelength range of 0.4~0.7um visible light those multispectral images are displayed on the display of this multispectral thermal imager in time, and then mixed with different transparency images to form an α-type multispectral image for analysis and interpretation Data about the gait behavior the temperature change of the footprint。

Description

System and method for analyzing gait footprint based on α-type multispectral image

Disclosure information: (1). This invention application case (hereinafter referred to as this case) is to disclose the Republic of China invention patent case No. I 666935 (including the U.S. patent certificate number US108481691B2 of the same case) against the previous inventor of the present invention, and the Republic of China invention patent case I This case is proposed after multiple experiments and simplifications and amendments based on the technical features of the hardware disclosed in No. 425292 (hereinafter referred to as No. I 425292); (2). This application is filed with priority of the Republic of China Invention Patent Application No. 109104728 [Animal harmless experimental method and its opaque experimental container].

The invention relates to a gait footprint analysis system, in particular to a data establishment method and system for capturing multispectral images of the gait footprints of the elderly.

According to the definition of the United Nations World Health Organization (WHO), the population over 65 is the elderly. When the elderly population accounts for more than 7% of the total population, this society is called an "ageing/aging society"; when it reaches 14% This society is called an "aged society", and when the elderly account for more than 20% of the population, this society is called a "super-aged society".

It is estimated that by 2020, Taiwan’s elderly population will reach 16.2%, which is second only to Japan, Hong Kong and Singapore in Asia. It is estimated that by 2050, all Asian regions, except the Philippines, will enter an elderly society, more than half of them. Taiwan’s leading Asian artists will enter a super-aged society, and Taiwan is one of them. By then, Taiwan’s elderly population will grow to 35.9%.

How to solve the problems and impacts caused by the aging society? How to respond to the challenges of an aging society? "Aging" is still considered as a "problem." The challenges that an aging population will bring include: increasing the risk of disease, the crisis of disability, the increased financial burden of caring for the elderly, and the discrimination and unfairness of the elderly. Problems (WHO, 2002).

Gait problems in the elderly are a common cause of dysfunction. Although the increase in age will cause some physiological functions to weaken and affect gait, some gait changes are not only due to factors of age but related to other diseases. In other words, the gait disorder of most elderly people is often the result of multiple factors.

Generally speaking, the elderly are most afraid of falls. They may fracture after falling. They may even need to stay in bed for a long time, which increases the risk of disability and death. The National Cheng Kung University Hospital and Yunlin University of Science and Technology have developed a "gait analysis" system that can effectively assess the risk of falls in the elderly and stroke patients, and reduce the risk of falls for the elderly through continuous exercise and rehabilitation.

According to experts and physicians from the Rehabilitation Department of the hospital, frail elderly people are a high-risk group of falls. Once they fall, they will increase the risk of disability and death. How to identify high-risk groups and intervene in a timely manner to effectively prevent the elderly from falling will be an important issue for the elderly society.

Through the "gait footprint" analysis system, the gait of chronic stroke patients and healthy adults can be distinguished, and it can also be used to distinguish the gait of patients who have fallen from those who have not fallen in chronic stroke patients.

Therefore, real-time analysis of the mobility of the elderly or patients is aimed at early detection and early intervention to reduce the risk of falls in high-risk groups. Under the guidance of an occupational therapist and fitness coach, practice weight-bearing exercises to make the pace more stable. Avoid falling, and then intelligently identify and analyze the gait, which will help improve the understanding and communication between the doctor and the patient!

Although walking speed has been used to predict the quality of life of the elderly, people who walk fast have better quality of life than people who walk slowly, but the premise of this conclusion is that the walking gait must be correct. Otherwise, blindly speeding up walking will increase the chance of falling, and may also accelerate the damage to the function of the knee joint and surrounding tissues.

Thanks to technology, we can now use photographic records and electronic trail analysis systems, even plantar pressure testing and dynamic temperature change thermal (image) images, to further perform quantitative foot print analysis to determine the quality of a person’s walking gait. how.

The parameters of gait footprint analysis include time and space parameters, kinematics parameters, and dynamic parameters. Among them, time and space parameters are particularly important for detecting the image classification of gait function, which can not only provide patients with Parkinson's disease as an example Gait function testing can also be used as one of the evaluation tools for the effectiveness of gait training.

According to statistics from the Chief Accounting Office, the number of unhealthy survival years in Taiwan is 8.8 years, and Taiwanese elderly people spend a lot of time in bed before they die; in addition, because of the prolonged life span, many of our elders suffer from dementia.

Obviously, many scholars and experts at home and abroad have proposed the research and development of gait analysis methods and systems. The purpose is to find and intervene early to help high-risk groups reduce the risk of falls, and to remove high-risk elderly and caregivers from the risk of falls. Falling may bring rescue from the risk of subsequent tragic life, reducing the physical and mental and financial pressure of caregivers in long-term care, and more importantly, enabling the elderly to have better health and quality of life.

The analysis method of gait involves two kinds of parameters, such as the time parameter of the gait and the space parameter of the gait.

Among them, the time parameters of gait include: walking speed per second along the direction of travel, frequency of steps taken per minute, and the elapsed time from the first contact of one foot to the first contact of the opposite foot The time elapsed from the first contact of one foot to the second contact of the same foot, the swing period of the observed foot off the ground in the gait cycle... etc.

Among them, the spatial parameters of the gait include: the distance of the two heels in the direction of travel when the observed heel touches the ground during walking to the other (or the same) heel touches the ground, and so on.

For example, the [Gait Analysis Method and System] of the Republic of China Invention Patent No. I657800 discloses that it includes multiple acceleration sensors. This method includes: for each time point and each acceleration sensor, calculating the root and square according to the acceleration value sensed by the acceleration sensor on the sensing axis; according to the first acceleration sensor and the second acceleration sensor Calculate the cross-correlation coefficient of the root and square of the sensor; calculate the first autocorrelation coefficient of the root and square of the first acceleration sensor; calculate the second autocorrelation coefficient of the root and square of the second acceleration sensor; and The cross-correlation coefficient, the first autocorrelation coefficient and the second autocorrelation coefficient are used to calculate the first-stage state index.

For example, the [Walking Assist Wearable Device and Walking Assist Method] of the Republic of China Invention Patent No. I637738 discloses: a walking assist wearable device for providing feedback information to the user on the road conditions ahead. The device includes: a wearing A tool for wearing; a plurality of distance sensors arranged at a plurality of positions of the wearing tool; a processor coupled to the distance sensors to use the distance sensors provided by the distance sensors from different heights , Horizontal angle, vertical angle and azimuth distance sensing information, compared to at least one stored information to obtain an environmental information; a storage module coupled to the processor to provide the stored information; a wireless module coupled to the The processor provides a wireless connection to at least one monitoring terminal; and a feedback module is coupled to the processor to provide feedback information based on the environmental information.

For example, the [Intelligent Suspension System with Gait Analysis Function] of the Republic of China Invention Patent No. I581829 discloses: an invention that can be applied to general exercise equipment or rehabilitation equipment to help users in rehabilitation training. A weight sensor and a displacement sensor are provided on the exercise device in the position area that can detect and present the user's weight change and gait change. The transmission mechanism of the exercise device is connected with a load that can restrain the user. It allows the user to support the exercise device through the smart suspension system. The weight sensor can detect the load-bearing capacity of the user’s lower limbs to adjust the support force appropriately, and the displacement sensor can detect and Analyze the user’s gait and provide real-time feedback, allowing the user to know the gait status of exercise or rehabilitation through visual feedback, and then make appropriate gait adjustments. The feedback signal can also be used as the operation control of the rehabilitation device For use.

For example, the [Thermochromic Gait Analysis System] of the Republic of China Invention Patent No. I578961, which discloses: a base for the subject to step on and walk, and can be adjusted according to the temperature of each foot contacted by stepping. Corresponding to produce a discolored area. The image capturing device can capture the image of the discolored area. The gait analysis device can receive and analyze the shape and color change of the image of each discolored area, and establish a pedaling pattern data for the sole corresponding to each discolored area. By analyzing the color change of the abutment being stepped on, more accurate foot pedaling information can be obtained, and the accuracy of the established walking gait data can be greatly improved. It is an innovative gait analysis with better accuracy. The system design is characterized by a flat plate on the base, and a thermochromic film that is covered and fixed on the top surface of the flat plate and can be temperature-sensitive and color-changing. In this embodiment, the flat plate is transparent, allowing the color change of the thermochromic film to be viewed from bottom to top.

Others, such as the Republic of China invention patent No. I579530 [Mobile device pedometer system and its gait analysis method], such as the Republic of China invention patent No. I549033 [Touch-sensitive gait analysis system], such as the Republic of China invention patent [Gait analysis device and running equipment using it] No. I517875, etc.

As mentioned above, the exposure of the prior art involves various sensors that are worn on the human body and/or installed on the trail. Obviously, it is easy to cause "mental burden" and psychological impact on the elderly of the subject. Accurate data.

In addition, as of the time of writing this invention, according to the patent information retrieval system of the Republic of China and its related global patent retrieval system, the keywords "multispectral thermal imaging camera" and "multispectral and gait classification" have not been retrieved yet. .

The [care system based on multi-spectral image analysis of elderly people's footprints] of this application discloses a multi-spectral thermal imaging camera that uses a multi-spectral thermal imaging camera to track and detect residues or display gait footprints when walking on a test trail. A Multispectral image, a method and device for analyzing and interpreting "normal behavior" for the elderly without wearing their bodies.

At present, in addition to the national defense and military, common thermal imagers used in civilian industries and other applications can capture the "thermal signal" of a target object and the "visible light image" of the target object. Two different images (spectrum) are fused (Fusion image) is a kind of thermal image (Thermal image), that is to say, the common thermal imager prevents the human eye from directly seeing the temperature distribution on the surface of the target object, and the conversion becomes the human eye can see the target The thermal image of the surface temperature distribution represented by the object; moreover, it can also capture the visible light image that the human eye can see, because common thermal imagers have two lenses, and one first lens can capture the target The "thermal image" of the object, another second lens can capture the "visible light image" of the target object.

First of all, in order to facilitate the description of the basic principles and mechanism of the multi-spectral thermal imaging camera and common thermal imaging cameras of the present invention (hereinafter referred to as the present case), please refer to the description of the color diagrams in Figure 1 to Figure 1 E to add learn.

Please refer to Figure 1 for an example of a real-world target photo; Figure 1A is a thermal image captured by a common thermal imager. Figure 1; Figure 1B is a thermal image captured by a common thermal imager. Photograph 2; Fig. 1C is a schematic diagram of the thermal image of the target object captured by the multi-spectral thermal imager of the present case; Figure 1 D is the thermal image diagram of the target object captured by the multi-spectral thermal imager of the present case.

As shown in Figure 1, it is a photo of a real-world target that can be seen by the human eye in the laboratory. There are four cups on the table, numbered 1, 2, 3, and 4 respectively. Among them, the glass cup No. 1 is inside. It contains cold water, the No. 2 glass contains hot water, and the No. 3 is an inverted opaque black cup. Among them, a near-infrared flashlight 31 with a hand held at the top of the No. 3 cup and a No. 4 ceramic cup contain heat. Water, among them, the No. 4 ceramic cup has a colorful landscape pattern 41 and a handle 42 on its body.

As shown in Figure 1A, a common thermal imager captures the thermal image of the target. From the color temperature label TL on the right side of the thermal image, it can be seen that the dark blue cold water 11 in the No. 1 cup is lower than "room temperature 25.4". °C (light blue)", so it means "cold" water;

The deep red hot water in the No. 2 cup is about 60C, so it is “hot water”; among them, the temperature of the black opaque cup body of No. 3 is slightly the same as the room temperature 25.4°C (light blue), and there is no obvious “temperature difference”. "Therefore, common thermal imaging cameras cannot capture the surface of an object with "no temperature difference". Therefore, the body of the No. 3 opaque black cup cannot be seen, but only its "very visible outline 311". This kind of contour 311 is also the "visible light bar" referred to by the "fusion technology" of common thermal imaging cameras.

But, why can I see the light green thermal image of "Human Hand and Flashlight 31"?

That's because the body temperature of the "hands" is slightly higher than the room temperature of 25.4°C; and the "flashlight 31" generates internal "slight heat" during use, which allows common thermal imaging cameras to photograph this "hands and flashlight 31" target light green的热像312。 的热像312.

As shown in Figure 1A, the thermal image 411 of the hot water in the ceramic cup No. 4, and the thermal image 411 of the colorful landscape pattern 41 on the ceramic cup body of the No. 4 ceramic cup can not be seen clearly.

As shown in Figure 1B, it is another enlarged thermal image 411 of Figure 1A showing the thermal image 411 with hot water in the ceramic cup No. 4. At this time, the thermal image 411 with "blurred edges" can be clearly seen. , This "blurred edge" thermal image 411 is a common phenomenon (missing) that all common thermal imaging cameras capture thermal images.

As shown in Figure 1B, it is obvious that the edge of the thermal image of a common thermal imager, compared with the image of visible light, has the phenomenon of "the edge curve is not obvious"! It is mainly caused by the temperature gradient effect. That is to say, the thermal image 411 with hot water in the ceramic cup No. 4 has the phenomenon of "the edge curve is not obvious"!

In order to solve the problem of "not obvious edge curve" of temperature gradient! , The engineers of FLIR, the largest thermal imager manufacturer in the United States, extracted the "clear lines" from the "visible light" image, and then superimposed it with the original thermal image to see the "edge lines" more clearly. The "clearer" thermal image 411 is FLIR's patented MSX fusion technology called Image Fusion.

It is obvious that common thermal imaging cameras have two different lenses that capture thermal images and visible light respectively.

Of course, in order to extract this "clear line", the second lens of a common thermal imager must add an ICF in advance before the visible light captured by the second lens enters the visible light image sensor (Image Sensor). Infrared Cut Filter) cuts off the near-infrared (light) Infrared in the incident light, and only allows visible light to pass through to capture pure color visible light images.

As a result, all common thermal imaging cameras cannot capture near-infrared images.

As shown in Figure 1C, the thermal image of the real target in Figure 1 captured by the multi-spectral thermal imager. Among them, this "iron red" image is also a kind of "palette" that common thermal images have "One of many (such as rainbow color, black and white, etc.) heat map color function.

As shown in Figure 1C, it is obvious that the black opaque cup No. 3 can be turned into a transparent cup 311 (you can also see an object 3111 in the cup); it also shows the color landscape pattern 41 on the body of the No. 4 ceramic cup. The thermal image 411 and the thermal image 412 on the body of the No. 4 ceramic cup, and the thermal image 421 of the handle of the No. 4 ceramic cup can also be seen.

From the obvious difference between Figure 1A and Figure 1C, it can be seen that the more common thermal imaging cameras with multi-spectral thermal imaging cameras have thermal imaging images that can take real-world images, including: (1). You can see "No. 3 black is not The transparent cup 311 and the object 3111 in the transparent cup 311 with the near-infrared shadow (picture) of the “transparent cup” are called the “perspective” function; (2). You can see the colorful landscape pattern on the “No. 4 ceramic cup” "41" thermal image 411, this thermal image 411 is as clear as the color landscape pattern 41 on the original No. 4 ceramic cup, and the thermal image 421 of the handle of the No. 4 ceramic cup can be seen; and (3). Can be seen The thermal image 412 of the "hot water temperature in the ceramic cup No. 4" is called the "clear" function, as shown in Figure 1D.

The above-mentioned (1)~(3) "perspective and clear" functions shown in Figure 1C can be displayed on the same monitor at the same time. This is called a "quick" function, because generally this kind of "perspective" The function of "clear and clear" requires two imaging devices, such as a common thermal imager and a near-infrared camera, to capture the images separately, and then display them as "switching" or "Picture-in-Picture PIP" on a different monitor.

Therefore, it shows that a multi-spectral thermal imager can take a thermal image with "fast, clear and transparent" functions than a common thermal imager.

Therefore, these "multi-spectral thermal imaging cameras are more common with thermal imaging cameras with superior technical features. They can indeed be applied to the "care system based on multi-spectral image analysis of elderly foot prints" in this case. The disclosure uses a multi-spectral imaging system. A thermal imager is a method and device for categorizing and interpreting an A multi-spectral image of an elderly person walking on a test trail.

As can be seen from Figure 1A and Figure 1B: the images captured by common thermal imaging cameras are in the two wavebands of "thermal image and visible light". Multi-spectral thermal imaging cameras, common thermal imaging cameras cannot show!

In order to further explain the technical solution of the multi-spectral thermal imager with the above-mentioned "fast, clear and see-through" function, please refer to the description of Figure 2 ~ Figure 2 C to further understand the related multi-spectral thermal imagers and common thermal images The spectrogram of the image captured by the instrument can further understand the differences and problems.

Please refer to Figure 2 for the schematic diagram of the spectrum captured by a common thermal imager, Figure 2A for the schematic diagram of the spectrum captured by the No. I 666935 thermal imager, and Figure 2 B for the thermal image of the No. I 425292 A schematic diagram of the spectrum captured by the instrument; and Figure 2C is a schematic diagram of the spectrum captured by the multi-spectral thermal imager of the present application.

In the above-mentioned spectra captured by the thermal imaging cameras in Fig. 2 to Fig. 2C, the ordinate is the light transmittance percentage; and the abscissa is the corresponding wavelength (unit is nm, where 1um=1000nm).

The above-mentioned spectra captured by the thermal imaging cameras in Figures 2~2C do not show the thermal image spectra containing the common "8~14um range", where the "8~ The "14um range" is called the far infrared (FIR, Far Infrared) thermal image. To simplify the description, the "8~14um range" thermal image spectrum is not drawn here, but only the different captured ones are drawn. Spectrum.

As shown in Figure 2, it is the range of "400nm~700nm" in the spectrum captured by a common thermal imager. Obviously, this is in the "visible light spectrum (VIS, visible)" range, because common thermal imagers are designed to capture Take the outline lines of the simple "visible light VIS" to merge with the "8~14um thermal image" to produce a clearer "8-14um" fusion thermal image. Therefore, the common thermal imager captures the "8~14um" thermal image. Two images of "~14um thermal image" and "400nm~700nm visible light" are shown in Figure 1A.

As shown in Figure 2A, the spectrum captured by Patent No. I 666935 [Micro thermal imager for enhanced near-infrared image capture] has "400nm~700nm VIS" + "700nm~1100nm" NIR range. Obviously , This is in the "visible light + near infrared (VIS+NIR)" range, because the second lens Lens2 of the I 666935 thermal imager has removed the "ICF, Infrafed Cut Filter originally set in common thermal imagers", Therefore, No. I 666935 captures the "700nm~1100nm" near infrared NIR part more than common thermal imaging cameras.

As shown in Figure 2B, although the spectrum captured by the thermal imager No. I 425292 also has a near infrared range of "700nm~1100nm", the "700nm~1100nm" near infrared range includes the "850nm ( 850nm±20nm)” near infrared. As its manual explains, this “850nm” near infrared is based on the “switching element and Action”, in which the “switching” action is represented by the solid line and the dashed line shown in the graph.

As shown in Figure 2B, the "switching" action can be changed to "Visible VIS" or "Visible VIS+850nm", which is what the industry calls the "Day & Night" mode. This mode structure is better than the second Figure C shows the switching element of "ICF and IPF two filters" and the extra "switching" action.

For example, Figure 2C shows the spectrum captured by a multi-spectral thermal imaging camera, which is obviously in the "visible light + near infrared (VIS+NIR)" range. However, it is worth noting that the near infrared range in this case is only in the "940nm (940±20nm)" near infrared range!

Why is it limited to the "940nm" near-infrared range?

The first reason is: if there is no near-infrared "940nm (940±20nm)", as shown in Figure 2, the multi-spectral thermal imaging camera in this case will not be able to capture the "near infrared" in the auxiliary perspective identification method. "The same clear contrast image; the second reason is: this "940nm (940±20nm)" near-infrared spectrum is completely invisible to the human eye.

It is revealed in the technical features of the specification No. I 666935 that the “visible and near infrared” images that can be captured by the No. I 666935 (as shown in Figure 2A) are formed by the “continuous spectrum” inputted by both, sometimes The image at the superimposition of "visible light and near-infrared" will be blurred.

If the "visible light and near-infrared" images can be processed separately into independent "visible light" or "near-infrared" images to form a discontinuous spectrum (as shown in Figure 2C), then when observing the gait analysis, A clearer recognition image can be obtained as shown in Figure 1C.

The multiple embodiments of this case do not involve professional clinical research on gait and foot print analysis. Therefore, only the description of the technical features of the gait and foot print analysis function of the elderly by the principle of the multi-spectral thermal imaging camera is described here.

The device of a multi-spectral image analysis system in this case is characterized by including a multi-spectral trail, a multi-spectral thermal imaging camera, and a near-infrared auxiliary light source module. However, these are still needed as the analysis system. Including the classification and interpretation by a method called "A multi-spectral image". This "A(α)" means "alpha blending", that is to say: the image captured by the multi-spectral thermal imager Multiple images undergo a method of transparency blending to form a superimposed multispectral image that can be more easily distinguished by observing researchers. This case is defined as "A multispectral image". Therefore, it can be seen that the disclosure of this case is a method and also A device.

The “multi-spectral trail” of the device in the embodiment of this case mainly explains: it is a kind of “walk” for tracking and detecting the walking of the elderly, and it uses the multi-spectral thermal imaging camera to capture more information on this “walk”. "Spectral image" is used as a method of tracking and detection, and then interpreted. This is to distinguish the technical solution of using multiple sensors (Sensors) in order to distinguish it from the prior art.

Among them, the material of this "walk" is invisible to human eyes (non-transparent visible light), which is also to distinguish the transparent board used in the previous technology, which allows the camera set up under the transparent board to capture the images of people walking on the transparent board. Gait foot prints.

The "multi-spectral thermal imaging camera" installed in the embodiment of this case mainly explains: This is because the thermal imaging camera of this case can capture three types of spectra of "VIS visible light + near infrared NIR + far infrared FIR", in order to distinguish it from common thermal imaging cameras. The technical characteristics of the two spectra of "VIS visible light + far-infrared FIR" can be captured; and the method in which the thermal imager in this case can capture multiple spectra is different from the method disclosed by the inventor himself in the prior art (I666935 and I425292). Among them, the NIR wavelength range captured by the thermal imager in this case is a narrow band spectrum of 940±20 nm, and the NIR wavelength range disclosed in the prior art (I666935 and I425292) is a broadband spectrum of 700 to 1100 nm.

The "near-infrared auxiliary light source module" of the device in the embodiment of this case mainly explains: it emits 940nm near-infrared.

So, why change to only use 940nm near infrared?

Because the elderly are walking on the "walk", then the material of this "walk" must be opaque! Otherwise, it will affect the mood of elderly people walking (may be distracted to watch the camera or other debris under this "walk", which will affect the accuracy of the measurement.

However, if the material of this "walk" is opaque! Then, how can the camera below this "walk" capture the gait footprints of the elderly people walking on the "walk"?

As the inventor of the invention patent No. I423676 [Monitoring Use of Coated Substrate Imaging], the invention patent No. I328593 [Method and Application of Infrared Transparent Black Plastic] and; the above No. I666935 [Enhanced The micro thermal imaging camera that captures images in the near-infrared], etc., have all revealed the production method of the opaque material related to this "walk", and will not be described in detail here.

Related to this "walk" opaque materials, such as coated polycarbonate (PC) and black polymethyl methacrylate (PMMA, commonly known as acrylic), etc., have opaque but visible light Infrared-permeable characteristics, among which "infrared-permeable" includes near-infrared emission with 850nm and 940nm as the center wavelength.

Among them, because the 850nm LEDs will emit red visible light (Red dot) when they are in action, the industry calls them "red bursts"; but when the 940nm LEDs are in action, they are completely invisible to the human eye! Therefore, in this case, in order for the elderly to walk on this "walk" and not see the cameras and red bursts under the "walk", the "walk" of opaque material is used. For the same reason, the 940nm near-infrared is correspondingly used!

In order to further understand the function of the technical features of this case, in addition to the above description of Figure 1 to Figure 1 D, please refer to Figure 3 and Figure 3A.

Please refer to Figure 3 for the thermal image captured by a common thermal imager and refer to Figure 3A for the thermal image captured by a multispectral thermal imager.

Among them, Figure 3 and Figure 3A are all based on the same real picture as an example. In the real scene, there is a ceramic cup with hot water (the cup body has a colorful pattern) and an inverted black opaque plastic cup.

As shown in Figure 3, the thermal image 30A of this visible real scene captured by a common thermal imager is obviously: one is that the plastic cup cannot be seen clearly (because the temperature is the same as the ambient temperature, there is no thermal image), and the other is Can't see the pattern on the body of the ceramic cup.

As shown in Figure 3A, the thermal image 30B1 of this visible real scene captured by a multi-spectral thermal imager is obviously: one can see the pattern of the ceramic cup body, and the other is to see the object inside the ceramic cup clearly. Pattern 30B2.

The thermal image 30A shown in Fig. 3 is actually not so blurry, because the “pure” thermal image of the hot water in the ceramic cup is captured in this embodiment.

The "pure" thermal image 30A is purely to show the temperature distribution of the hot water in the ceramic cup. The temperature gradient causes a blurry image to the human eye.

In order to solve this blurry image, the following figure illustrates.

Please refer to Figure 4 for the schematic diagram of the FLIR thermal imager factory solution and Figure 4A for the schematic diagram of the FLUKE thermal imager factory solution.

The above-mentioned definition of "940nm" means "does not include the human eye visible or recognizable near-infrared", that is to say, it excludes the 850nm near-infrared covered by Figure 2A and Figure 2B!

The above-mentioned near-infrared with "940nm" as the center wavelength is also defined as "940±20nm" in this case, because the "±20nm" is the reference error range of IR-LEDs manufacturers' products. Its characteristics are Near-infrared that is "completely invisible to the human eye"! Among them, other near-infrared particle products with 960nm and 980nm as the center wavelength that are produced on the market should also be equally regarded as the "940nm as the center wavelength" family.

As shown in Figure 4, the FLIR thermal imaging camera factory's method to solve the blurry thermal image is to extract the "contour lines" of the visible light real scene and then merge with the pure thermal image (Fusion) solution, FLIR discloses MSX patented technology.

As shown in Figure 4A, the method of FLUKE Thermal Imager Factory to solve the fuzzy thermal image, it is a solution method that mixes the visible light real scene and the pure thermal image, the IR-FUSION patented technology disclosed by FLUKE.

In the embodiment of this case, in order to solve this ambiguous image, the technical solution adopted is to avoid the "multi-spectral transparency blending" method, which is considered by the patents of MSX and IR-FUSION, and is used to assist the interpretation of multi-spectral image analysis. system.

Object of the present application is to provide a multi-spectral image analysis system, wherein, while capturing and analyzing may comprise a target object in the far infrared wavelength range directed to the FIR 8 ~ 14 u m, the wavelength in the visible range of 0.4 ~ 0.7 u m; and an image of the three spectral wavelength range of the near infrared (NIR) of 0.94 u m and the like.

Another objective of the present application is to provide a device for a multi-spectral image analysis system, which includes an opaque walkway, a multi-spectral thermal imaging camera, and a near-infrared auxiliary light source module.

Another purpose of this application is to provide a device and method of a multi-spectral image analysis system for detecting and tracking information information of high-definition contrast gait behavior analysis and foot print temperature changes of the elderly.

Another object of the present invention is to provide a benefit that can produce a simplified structure to facilitate the promotion of medical teaching hospitals and campus biomedical departments.

Another object of the present invention is to provide a device and method of a multi-spectral image analysis system, which is used to acquire a model of a large amount of experimental data.

First of all, in addition to the illustrations and descriptions in Figures 2 to 2C, etc., in order to further understand the method of the embodiment, please refer to Figure 5.

Please refer to Figure 5 for the schematic diagrams of the common thermal imager, thermal imager I 666935, thermal imager I 425292, etc.

As shown in Figure 5, the spectrum captured by a common thermal imaging camera is shown in Figure 4. The second lens Lens2 in the figure has a filter "ICF, Infrafed Cut Filter"; What the thermal imager reveals that the second lens Lens2 has been removed from the ICF and replaced by a transparent glass 39 without filter function. Therefore, the near infrared on the second lens Lens2 of a common thermal imager cannot enter. It allows visible light to enter. Therefore, the captured spectrum is shown in Figure 2; Figure 4A of the content disclosed in No. I 666935 captures more near-infrared "700nm~1100nm" than common thermal imaging cameras. Part, therefore, the spectrum captured by No. I 666935 is shown in Figure 2A.

As shown in Fig. 5, in the first image C of the content disclosed in No. I 425292, a "switching" action and component must be added to capture a "near infrared image", that is: a dual A moving plate in the filter set 20 pushes the two filters of ICF and IPF (as shown in Figure 6 and Figure 6A), but the multi-spectral thermal imaging camera in this case omits these redundant related components. Obviously, the multi-spectral camera in this case The hardware structure of the thermal imager is simpler than that of the common thermal imager, the thermal imager exposed by No. I 666935, and the thermal imager disclosed by No. I 425292.

In this way, it can be clearly distinguished from the technical features disclosed by common thermal imaging cameras, No. I 666935 and No. I 425292 related thermal imaging cameras. Obviously, the technical characteristics of the multi-spectral thermal imaging camera in this case are common thermal imaging cameras, What I 666935 and I 425292 do not have!

Then, how can the second lens in this case capture "0.4~0.7um visible light image + 0.9um (940nm) near infrared" (as shown in Figure 1C)?

Among them, the main reason is that the second lens in this case is pasted with an optical coating filter (light) that can pass "0.4~0.7um visible light image" and "central wavelength 0.94um (940nm) near infrared" dual band (electromagnetic wave). NIR940.

The idea of sticking an optically coated filter (light) on the second lens of this case is related to the common thermal imager, the thermal imager No. I 666935 and No. I 425292, etc. In many examples of experiments such as thermal imaging cameras, such as in the campus teaching experiment in Figure 1~Figure 1D, it was accidentally discovered that it should be possible to "convert the use" based on the characteristics found in the experiment, and proposed that it is suitable for "elderly elders" Modification and application of "Footprint Multispectral Analysis System"!

Please refer to Figure 6 for a schematic diagram of the dual-lens image capturing process of a multi-spectral thermal imager.

As shown in Figure 6, the dual-lens of the multi-spectral thermal imager (the thermal imager in this case) includes: a first lens and a second lens.

Among them, the first lens has the same function as the common thermal imager and the first lens disclosed by the I 666935 thermal imager. It is responsible for capturing the far-infrared band in the range of "8~14μm". The sensing and control circuit of the planar sensor FPA and the processing of the subsequent processing circuit 100A are finally processed in Image Fusion. Therefore, common thermal imaging cameras and thermal imaging cameras No. I 666935 are disclosed here. Another detailed description.

As shown in Figure 6, where the second lens of the multi-spectral thermal imager, if there is a "near-infrared auxiliary light source" that is aimed at the same target as the second lens, it is marked as (Yes) in the flowchart. Then the target object will be illuminated by its near infrared (light) and the target object will be illuminated by its visible light. The reflections of the two will be reflected back to the second lens through a filter with the symbol V940, and then enter the second lens. The image sensor in the lens senses the imaging output.

At this time, the output of the multi-spectral thermal imager is the "8~14μm" far-infrared captured by the first lens, and the output "0.4~0.7μm+0.94μm" captured by the second lens. The final two-lens capture Take and re-fusion, that is to say, what this second lens captures is visible light and near-infrared with "940nm" as the center wavelength.

Among them, if the second lens of the multi-spectral thermal imaging camera does not have a "near infrared auxiliary light source" and the second lens captures the same target, if it is marked as (No) in the flowchart, then the target Only after being irradiated by the visible light, it is reflected back to the second lens and passed through a filter with a symbol of V940, only the visible light of "0.4~0.7μm" is output and then enters the image sensor in the second lens for sensing Imaging output.

Among them, in other embodiments, it was found that even without the "near-infrared auxiliary light source" projecting near-infrared, the second lens sometimes appeared to capture the "faint near-infrared" image of the target!

Why do I see the "faint near-infrared" image of this target?

This may be due to the presence of natural near-infrared in the daytime environment, but it is impossible for natural near-infrared to occur in the dark like during the day!

For example, "V940" in Figure 6 refers to a dual-band filter (light) that can pass visible light (Visible band) and near-infrared band with a center wavelength of 940nm.

This dual-band filter is an optical coating filter commissioned by a professional coating factory to undergo coating processing. According to the sample provided by the manufacturer, the measurement error is about ±20nm. Therefore, the specification of this case also defines the above-mentioned "940nm as the center wavelength" "940nm±20nm" or "940nm±20nm" is also defined as the center wavelength of "940nm"; and 940nm=0.94um.

Therefore, it can be seen that the multi-spectral thermal imaging camera can be used as an identification method for animal drug experiments because it can capture the "far-infrared + near-infrared + visible light" images at the same time (as shown in Figure 4), that is, it can Capture the three-band image of "8~14μm far infrared +940nm near infrared +400~700nm visible light" at the same time!

In order to simplify the structure of the multi-spectral thermal imager, the optical coating filter attached to the second lens of the multi-spectral thermal imager is like the V940 in Figure 6, which also reduces the "switching action of No. I 425292 as described in Figure 3. It and the required components".

The optical coating filter attached to the second lens of the multi-spectral thermal imager is like the V940 in Figure 6, which also enables the dual-lens of the first lens and the second lens of the multi-spectral thermal imager to be displayed on the same screen of the thermal imager at the same time Three wavebands of "thermal image, visible light and near-infrared" images are produced.

So, how did the multi-spectral thermal imaging camera with the above-mentioned purpose and function come into being?

Please refer to the first schematic diagram of the device of the embodiment of the multi-spectral thermal imager in FIG. 7; and the schematic diagram 2 of the device of the embodiment of the multi-spectral thermal imager in FIG. 7A.

As shown in FIG. 7, the device of the embodiment of the multi-spectral thermal imager includes a multi-spectral thermal imager 5A, an object 5B, and a near-infrared auxiliary light source 5C.

As shown in Figure 7, the multi-spectral thermal imager 5A further includes a first lens module 5A1 (hereinafter referred to as the first lens 5A1), a second lens module 5A2 (hereinafter referred to as the second lens 5A2), and a body 5A3. The front end of the body 5A3 is provided with a dual lens consisting of a first lens 5A1 and a second lens 5A2. The first lens 5A1 is the same as the first lens Lens1 in Fig. 4A as described in No. I 666935, no further details Narrated.

Among them, the far infrared (FIR, Far Infrared) captured by the first lens 5A1 enters the focal plane array (FPA) 5A31 thermal image sensor 5A32 (Thermal Image Sensor Chip) in the body 5A3 for induction imaging.

The focal plane array (FPA) 5A31 sensor is an uncooled infrared focal plane array FPA developed by Texas Instruments after the 1990s. Because the thermal imaging sensors used by major manufacturers are different, so, The thermal image sensor 5A31 in the thermal imager 5A is not limited to this.

Special attention should be paid to the part of the second lens 5A2:

As shown in Figure 7, inside the second lens 5A2 of the multi-spectral thermal imager 5A, a coated optical filter (light) 5A21 is attached. This filter 5A21 is the same as the V940 filter described in Figure 4, with its characteristics It is a dual-band filter that only allows two bands of near-infrared + visible light (400~700nm) with a center wavelength of 940nm to pass. This V940 filter is on a dielectric transparent film that does not absorb any The optical coating method is coated with a mold material with a thickness of about 0.2mm, so the second lens 5A2 of the multi-spectral thermal imager 5A can capture the spectrum as shown in Figure 2C.

Therefore, as shown in Figure 7, the dual-lens of the multi-spectral thermal imager 5A can simultaneously capture three-band images of "8~14μm +940nm +400~700nm" at once! As shown in Figure 1C.

Among them, this filter 5A21 (such as the V940 filter described in Figure 4) does not need to rely on it as in the I 425292 "requires a double filter set 20 of a moving plate 22a to push the two ICF and IPF. The action of the "filter" and its components.

Among them, the second lens 5A2 of the multi-spectral thermal imager 5A involves some parameters of the lens specifications, such as the field of view (FOV) and the lens focal length, which are outside the scope of the patent application in this case. Those with ordinary knowledge can customize the specifications according to their needs. .

As shown in Figure 7, the circuit control 5A33 in the body 5A3 of the multispectral thermal imager 5A is the control circuit for processing the FPA focal plane array 5A31, and the circuit control 5A33 is the control circuit for processing the image sensor, the image fusion device 5A34 It is a fusion processing (soft and hardware) circuit after processing the image of the object 5B captured by the first lens 5A1 and the second lens 5A2 of the multi-spectral thermal imager 5A.

For example, the near-infrared auxiliary light source 5C in Figure 7 is the same as the near-infrared flashlight 31 in Figure 1. It is then reflected to the second lens 5A2 of the multi-spectral thermal imager 5A for imaging.

For example, Fig. 7A is a diagram of another embodiment in Fig. 7. The difference from Fig. 7 is only that there is an obstacle between the "object 5B and the second lens 5A2 of the multi-spectral thermal imager 5A" 5D, the material of this obstruction 5D is the same as the material of the inverted black opaque cup shown in No. 3 in Figure 1, at least it is a material that allows the near-infrared light 5C111 projected by the near-infrared auxiliary light source 5C to pass through. Among them, the material of the obstacle 5D can be plastic or glass, that is to say, as disclosed in the US Publication No. US 219/002831 A1 disclosed by the present inventor, the materials of the 9D and 9E drawings are the same, or they can be coated glass. Plates and other materials that can penetrate near infrared, as disclosed by the present inventor No. I 423676 [Monitoring Uses of Imaging of Coated Substrates].

Of course, this can be formed by a variety of materials, for example, it can also be "red transparent cellophane and blue transparent cellophane" pasted on a piece of transparent glass or transparent plastic to form an opaque obstacle 5D; and in recent years New near-infrared absorption materials developed, such as OPTLION developed by TOYO VISUAL in Japan.

Please refer to Figure 8 for a schematic diagram of an embodiment of a multispectral thermal imager; Figure 8A is a schematic diagram of a liquid crystal display of a multispectral thermal imager; Figure 8B is a schematic diagram of the top of the multispectral thermal imager; and Figure 8C is an activity Schematic diagram of box 5C1.

As shown in Fig. 8, an embodiment of a multi-spectral thermal imager (or referred to as a handheld thermal imager 50) includes a combination of a multi-spectral thermal imager 5A and a near-infrared light-emitting source module 5C .

Among them, the front of the multi-spectral thermal imager 5A includes a first lens 5A1, a second lens 5A2, a lens frame 5A4, and a distance sensor 5A41 (which can detect the distance from the second lens 5A2 to the object 5B) , A recording button 5A5 (can record the images captured by the multi-spectral thermal imager 5A).

The near-infrared light-emitting source module 5C includes a movable frame 5C1, a near-infrared light-emitting diode 5C11 and a fixed frame 5C2 are arranged in the frame, and the movable frame 5C1 and the fixed frame 5C2 are connected to each other by a connecting column 5C3. At the same time, the fixed frame 5C2 is provided with screw holes 5C21 on the side of the frame, and the fixed frame 5C2 can be locked on the outer lens frame 5A4 with screws, as shown in the thermal imager application device (handheld thermal imager 50).

Among them, in the two frames of the movable frame 5C1 and the fixed frame 5C2 of the near-infrared auxiliary light source 5C, there is a circular cavity (as shown by the thick arrow line symbol) that matches the size of the lens frame 5A4 to avoid "blocking the lens" In the outer frame 5A4, the dual-lens capture image direction and range accuracy" affect the action.

Figure 8A is a liquid crystal display (LCD) 5A6 for displaying the fused images captured by the first lens 5A1 and the second lens 5A2 of the multispectral thermal imager 5A, the measurement data of the distance sensor 5A41, and the control circuit Other data (such as LOGO) images such as the displayed date and time, the color temperature state of the color temperature bar TL (such as Figure 1 A, Figure 1 C, and Figure 1 D) and other data (such as LOGO).

Among them, on the liquid crystal display (LCD) 5A6 in Figure 8A, it can quickly and simultaneously display all the images of the "thermal image, posture change and gait analysis of the animal under test" at the same time. This is the case. One of its technical characteristics, as shown in Figure 1C.

As shown in Figure 8B, the top of the handheld multi-spectral thermal imager 5A is the input/output port 5A7, which basically includes at least the T type USB port for charging input, the video output port (TV out), SD memory card, etc. Changes in market demand, for example, when used in animal experiment teaching, it can use its image output port to connect to a larger display screen for observation and discussion by multiple people; and it can save all relevant image data to its SD memory The card is further used as a large amount of image data required by artificial intelligence.

As shown in Figure 8C, IR-LEDs near-infrared light-emitting diodes 5C11 are arranged in the grooves between the frames of the movable frame 5C1. The emission wavelength of these IR-LEDs is "limited" to the near-infrared that is completely invisible to the human eye, for example, Near-infrared with a center wavelength of 940nm; however, its emission power is "not limited" and can be determined according to product requirements.

Among them, the upper part of the groove between the frames of the movable frame 5C1 is further covered with a diffusion plate 5C12 with a diffusion function, which is suitable for the small animal experiment box 71 for closer observation.

Among them, the upper part of the groove between the frames of the movable frame 5C1 is further covered with a polarizer with a polarizing function, which is suitable for capturing near-infrared images without reflection interference for further observation.

Then, the above-mentioned multi-spectral trail, a multi-spectral thermal imaging camera, and a near-infrared auxiliary light source module as the analysis system still need to include analysis and interpretation by a method called "A multi-spectral image". This "A" means "alpha blending", which means that multiple images captured by a multi-spectral thermal imaging camera are subjected to a transparency blending method to form a system that can be more easily interpreted by observation researchers. The superimposed multispectral image is defined as "A(α) multispectral image" in this case.

What is Alpha Blending?

As known from the foregoing: common thermal imaging cameras have two imaging lenses, one captures the thermal image of the object, the other captures the visible light image, because the visible light image is usually clearer than the infrared thermal image, but these two different images The parallax produced by the combination of images is sometimes unreliable. What is really clearer is that the two images automatically overlap each other (as shown in Figure 4A).

Since the Field of View (FOV) of two adjacently arranged imaging lenses will have overlapping characteristics, according to the offset of the center of the two lenses, the two images are aligned and the image with the smaller field of view is superimposed on An image with a larger field of view. In this way, clear images with different zoom scales can be provided, and it can be ensured that the images can be smoothly presented during the zooming process.

As shown in Figure 4 above, the fusion technology of visible light and thermal image is to extract the obvious visible light lines from the visible light VIS image, and then merge it with the pure thermal image FIR to form an MSX thermal image.

As shown in Figure 4A above: Infrared Solutions Inc., a subsidiary of Fluke, USA, has developed a new infrared technology called IR-Fusion™, which can mix visible light pixels and infrared thermal image pixels on a single display. To solve the problem of parallax when combining images from separate visible light and infrared optical elements.

Among them, the IR-Fusion technology is to automatically correct the parallax of the visible image and adjust its size to match the infrared thermal (image) image. Therefore, the infrared thermal image and the visible image can be overlapped with each other and displayed on the display camera. Since the infrared image and the visible image are matched pixels of the camera, the operator can choose to view the visible image alone, the infrared image alone, or a hybrid (fusion) combination of the two.

The method of mixing images in the aforementioned IR-Fusion technology is similar to an alpha blending technology. The "A(α)" multi-spectral thermal imaging involved in this case is also an alpha blending technology. Among them, IR- Fusion technology is the transparency blending of "VIS+FIR"; the "A" multi-spectral thermal image of this case includes the transparency blending of "VIS+NIR940+FIR", as shown in Figure 9.

Please refer to Figure 9 for a schematic diagram of the process of A multi-spectral thermal image formation.

The heat from the first lens case multispectral thermal imager (Lens 1) captured by the image pattern (FIR = 8~14 u m) as its background a second lens (Lens 2) visible light images captured (VIS = 0.4 ~ 0.7 u m ) + near-infrared imaging (NIR = 0.94 u m) as the foreground in FIG. (but are not limited to what is foreground or background), this superimposed foreground on the background, After the processing of transparency blending, a kind of "A multi-spectral thermal image" is generated, where "A" stands for (alpha α ), where the alpha value is defined as the degree of transparency, and if the alpha value is 1 It is completely opaque, and the superimposed A multi-spectral thermal image is "VIS+NIR" or "VIS" or "NIR"; it is completely transparent with the α value 0, and the superimposed A multi-spectral thermal image The image is pure thermal image.

Furthermore, the A value of the A multi-spectral thermal image is between 0.0 and 1.0, for example, the α value is 0.3, then most of the thermal image of the foreground image in the A multi-spectral thermal image can be transparent, but not completely transparent. Among them, The alpha value contains 0 and 1 (or 0%~100%). If the A multi-spectral thermal image in the transparency is output to the monitor of a corresponding multi-spectral thermal imager for observation, it will be easier to find the most Thermal image that is beneficial to "interpretation and analysis".

Figure 9 is a schematic diagram of the process of A multi-spectral thermal image formation. Steps S90~S96 are introduced as follows:

S90: The thermal image (FIR=8~14nm) captured by the first lens (Lens 1) of the multi-spectral thermal imager is the same as that of a common thermal imager, and will not be described in detail here.

Among them, the image captured by the second lens (Lens 2) of the multi-spectral thermal imaging camera may include 0.4~0.7um VIS (visible light) and 0.7~1.0um NIR (near infrared) (such as the first 2 Figure C).

S91: In the environment in front of the second lens, VIS should be greater than NIR during daytime or indoor lighting, but at night or when the light is insufficient, that is, the second lens may have both VIS and NIR in its environment. Cannot be captured by the second lens for imaging.

Because the image captured by the second lens may contain three images "VIS" or "NIR" or "VIS+NIR", among which, if VIS is greater than NIR, the image captured by the second lens The image is "VIS"; if VIS is less than NIR, the image captured by the second lens is "NIR"; if the difference between VIS and NIR is not significant, the image captured by the second lens is "VIS+NIR".

S92: Regardless of whether it is illuminated in the daytime or indoors or in an environment with no lighting at night, if you want to obtain the special conditions of "NIR greater than VIS" or "NIR + VIS", then you need to project NIR from the outside. , Can only be achieved.

S93: If NIR is to be projected from the outside, a near-infrared NIR auxiliary light source module is usually added. In this embodiment, the near-infrared auxiliary light source uses 1~5w IR LEDs (infrared diodes) .

S94: When the NIR projected by the near-infrared auxiliary light source is too strong, it may affect the A multi-spectral thermal image to produce excessive "exposure" to the target, and the identification is not clear. In this case, the NIR auxiliary light source module is required. Dimmer to adjust the strength of its NIR.

S95: The images captured by the first and second lenses of the multispectral thermal imaging camera may include 8~14um far-infrared FIR, 0.4-0.7um visible light VIS, and 0.7-1.0um near-infrared NIR , Finally, we are using "FIR+VIS" and "FIR+NIR" and "FIR+VIS+NIR" for transparency blending to form A multi-spectral thermal image.

Among them, it should be noted that: NIR here refers to near-infrared with a wavelength of 940nm!

S96: Therefore, the multi-spectral thermal image processed by transparency mixing is called A multi-spectral thermal image, which includes: "FIR", "VIS", "NIR", "FIR+VIS", "FIR+NIR" , "FIR+VIS+NIR", etc., a plurality of different single-band or dual-band or three-band images, this embodiment is defined as A multi-spectral thermal image or α multi-spectral thermal image.

Generally, for the function of Alpha blending, most of the known modes are the mixing of "RGB+Grayscale". For example, the American thermal imager manufacturer FLUKE "RGB+Grayscale+Thermal The image can be said to be a mixture of "RGB + grayscale + thermal image + near infrared". Obviously, the function of Alpha mixing in this embodiment is quite different from the conventional mode. The input of infrared directly affects the Alpha value of the "gray scale", forming an alternative visual effect of different mixed images. This makes it possible to obtain a spectrum identification image with clearer and more distinct features in this embodiment.

Since this case was not set up for actual participation at the time of writing, it was implemented only with laboratory data (as shown in Figure 4 and Figure 4A).

Please refer to Figure 10 for a basic schematic diagram 1 of transparency blending in this embodiment, and Figure 10A for a basic schematic diagram 2 of transparency blending in this embodiment.

In this embodiment, the thermal image (FIR=8~14nm) captured by the first lens of the multi-spectral thermal imager is basically used as the background image and the visible light image captured by the second lens (VIS = 0.4 ~ 0.7 u m) + near-infrared imaging (NIR = 0.94m) FIG as foreground, the foreground superimposed on this background, the transparency of mixing after treatment, and then produce called "a multispectral Thermal image".

As shown in Figure 10, there is VIS visible light (a ceramic cup with hot water, but the cup with visible light cannot see the water in the cup) as the foreground layer. This VIS visible light is multiplied by the alpha channel and superimposed on it. On the FIR, the thermal image of the water ceramic cup becomes a simple α (A) multi-spectral thermal image.

As shown in Figure 10A, where the α value (1~0) is set to 100%, 80%, 60%, 40%, 20%, and 0%, the five A multi-spectral thermal images displayed (user It can be adjusted by pressing the "UP" and "DOWN" function keys on the multi-spectral thermal imager in the designated mode. Among them, if the pixel of the foreground image (Pixel) is "transparent" (that is, its alpha < 1) Then, the pixels of the background layer (Pixel) should "show through". In fact, superimposing the foreground layer of the same size (otherwise the stretching action is required) on top of the background layer, which reduces the value of α It will make the color gradually darker, which is to make this spectral image produce A multi-spectral thermal image with different transparency.

As shown in Figure 10A, it is a set of different α values and the various images displayed by the thermal imager under different "palettes", but it does not affect the characteristics displayed by the transparency blending.

Please refer to Figure 11 for a schematic diagram of visible light and thermal image transparency blending; Figure 11 for a schematic diagram of visible light insufficient and thermal image transparency blending.

In order to further illustrate the concept of transparency mixing, the following example also cite an object (a cup containing hot water) as an example to illustrate the use of a multi-spectral thermal imaging camera to shoot this object under sufficient visible light and insufficient visible light (night) environment, so Shows the phenomenon of transparency blending.

As shown in Figure 11, the hot water in the ceramic cup occupies about seventy-fourths of the cup. The visible light of the ceramic cup is multiplied by an α value of about 40% to form a VIS image 111 of the ceramic cup under the α value. .

As shown in Figure 11, the hot water in this ceramic cup occupies about seventy-fourths of the cup. The thermal image of the ceramic cup is multiplied by an alpha value of about 100% (indicating an incompletely transparent solid body) to form this The FIR thermal image 112 of the ceramic cup under the α value.

As shown in Figure 11, finally, the VIS image 111 is superimposed on the FIR thermal image 112 to form an alpha multi-spectral thermal image 113 of the ceramic cup.

Similarly, as shown in Figure 11A, where the hot water in this ceramic cup occupies about seven minutes full of the cup, the ceramic cup’s lack of visible light BLK (because of the lack of visible light, the image is not clear or appears dark) multiplied by approximately After an α value of 40%, the VIS image 114 of the ceramic cup under the α value is formed.

As shown in Figure 11A, where the hot water in the ceramic cup occupies about 70% of the cup, the thermal image of the ceramic cup is multiplied by an alpha value of about 100% (representing an incompletely transparent solid body) to form The FIR thermal image of this ceramic cup at the value of α is 115.

As shown in Figure 11A, finally, the VIS image 111 is superimposed on the FIR thermal image 115 to form an alpha multi-spectral thermal image 116 of the ceramic cup.

As shown in Figure 11 and Figure 11 A, where the Alpha value is between 0 and 1, or between 0% and 100%, the alpha blending technology that superimposes the foreground image on the background image also has many public documents. There are a variety of different pixel (Pixel) level calculation methods, but there is no such calculation method after adding the alpha value to the near-infrared.

To further emphasize the important functions and features of the calculation method in this case only after adding the alpha value to the near-infrared, please refer to the thermal image description of Figure 12~Figure 12 B of the embodiment of this case.

Please refer to Figure 12 for a thermal image diagram of an iced Coca-Cola soda; Figure 12A is a thermal image diagram of a glass beaker poured with ice-cold cola; Figure 12B is a thermal image diagram of a coke bamboo chopsticks in a see-through glass beaker; Figure 12C is a schematic diagram of a visible light image of a person's head; Figure 12D is a schematic diagram of a thermal image of a human head; Figure 12E is a schematic diagram of a thermal image of a human head and Figure 12D is a schematic diagram of a thermal image of a human head two.

As shown in Figure 12, there is a beaker with hot water on the left and a bottle of frozen Coca-Cola soda on the right. The beaker with hot water (orange) on the left is just to prove the Coca-Cola soda on the right. It is cold (dark black). From the “color temperature indicator bar” on the right side of the picture, the highest temperature is 68C and the highest temperature is 4C. It can also be known that the Coca-Cola soda is cold.

As shown in Figure 12A, the thermal image of a glass beaker with ice-cold Coke is obviously the same as Coca-Cola soda in real visible light. It is also an opaque black liquid to the human eye. Then insert a wooden chopsticks into this liquid. Only the chopsticks above the liquid can be seen, but the chopsticks inside the liquid cannot be seen (as shown in the picture).

As shown in Figure 12B, when poured into a thermal image of a glass beaker with ice-cold cola, you can suddenly see the chopsticks inside the liquid (as shown in the figure).

As shown in Figure 12B, you can suddenly see the "perspective" function of the chopsticks inside the liquid, which is a function that other common thermal imaging cameras do not have!

As shown in Figure 12C, it is a visible light image of a person’s head. In the picture, this person’s eyes have a pair of sunglasses (sunglasses). Therefore, visible light and human eyes cannot see this person’s eyes. Among them, this person wears a dark color. sweater.

As shown in Figure 12D, you can clearly see that there are four white squares on the dark sweater, but you still can't see clearly the person's eyes.

As shown in Figure 12E, in addition to clearly seeing the four white squares on the dark sweater, the person's eyes can also be seen clearly.

As shown in Figure 12B, Figure 12D and Figure 12E above, we can understand the "see-through" function of the multispectral thermal imaging camera in this case, that is to say, the alpha multispectral image of this case and other common thermal images The instrument has different and unique principles (including the perspective function) to compose the alpha multi-spectral image.

Then, how did the "perspective" function in Figure 12B, 12D, and 12E come about?

The answer is shown in the previous figures and descriptions of Fig. 2C, Fig. 3A, Fig. 6, Fig. 7A, Fig. 7 and so on, and will not be further described this time.

In the actual test of the alpha multi-spectral image in this embodiment, the projection of the near-infrared on the target object may cause different degrees of "absorption, reflection or diffusion" effects, which indirectly affects the new image and its vision produced by different transparency blends. Effect.

In order to reduce the indirect influence of the above-mentioned different degrees of "absorption, reflection or diffusion" effects, the near-infrared auxiliary light source 5C of this embodiment is turned on (ON), and a dimmer (as shown in Figure 9) is used to adjust the near-infrared NIR to be different. The intensity of the above-mentioned multi-spectral thermal imaging camera in this case, under the adjustment of the dimmer, the different images captured by it are suitable for a simple mathematical mode such as "NIR-VIS=ΔL", where ΔL< 0 (defined as visible light VIS) or = 0 (defined as visible light VIS + near infrared NIR) or> 0 (defined as near infrared NIR).

Obviously, the multi-spectral thermal imager 5A display 5A6 with α multi-spectral imaging function can display: FIR thermal image, VIS visible light, NIR near infrared, FIR thermal image + VIS visible light mixed α image, FIR thermal image + NIR near Infrared mixed alpha image, FIR thermal image + VIS visible light + NIR near infrared mixed alpha image.

That is to say: when taking alpha multispectral images of gait and footprints for elderly people, the parameters that interfere with the walking trail and its surrounding environment should be adjusted in clinical experiments, taking into account the above-mentioned parameter adjustment of the ΔL mathematical mode, and multiple shots should be taken. Alpha multispectral image.

Of course, the collection and generation of alpha multi-spectral images of these different degrees, as another case of artificial intelligence AI processing big data data will continue to be implemented in the future.

To sum up the discussion above, a number of embodiments of this case are given as an example.

Please refer to Figure 13 for a schematic diagram of an embodiment; Figure 13A is a schematic diagram of a safety concave walkway; Figure 13B is a schematic diagram of a thermal image of a footprint; Figure 13C is a schematic diagram of a near-infrared image of the footprint; and Figure D is a schematic diagram of gait foot print temperature analysis.

In many embodiments of this case, most of the thermal images, visible light and near-infrared images, including Figure 13 and Figure 13 B~D, were captured and recorded by the multi-spectral thermal imager by experts and physicians. analysis interpretation explanation, the case of multispectral thermal imager only for the object is captured, namely: for the wavelength range of the target object in the far infrared thermal image FIR 8 ~ 14 u m, the wavelength range of visible light VIS 0.4 ~ 0.7 u m visible image, and the image in the near infrared wavelength range of near infrared NIR 0.94um does not involve gait studies footprint analysis, therefore, only the technical features described herein the principles of multi-spectral imager and function.

As shown in Figure 13, a tested elderly person (elderly) 130 walks on a multi-spectral walkway 131. The material 1311 of the multi-spectral walkway 131 has two types. The first type is formed of "metal-coated or modified" plastics. ; The second category is the formation of metal plates with high thermal conductivity.

Among them, the first type of metal-plated film is SiO ₂ and TiO ₂ alternately evaporated to form a PC plastic board with 20% visible light and 80% near-infrared transmittance, such as the inventor’s Republic of China Invention Patent No. I423676 [Monitoring use for imaging of coated substrates] The first type of modified plastic is modified into a plastic plate that can transmit infrared but not visible light. For example, the inventor’s Republic of China Invention Patent No. I328593 [Transparent The production method and application of infrared black plastic] have been exposed, and will not be described in detail here.

Among them, the second category is metal plates with high thermal conductivity, such as aluminum metal (aluminum-based composite material), copper and silver, etc., and its thermal conductivity is preferably higher than 250 Wm ^-1 K ^-1 , and its high thermal conductivity is easy In the multi-spectral corridor 131, a thermal image 1301 of the more obvious footprint temperature is left.

As shown in FIG. 13, more than one multi-spectral thermal imager 132 can be set above and below the multi-spectral walkway 131 as appropriate.

As shown in Figure 13, the multi-spectral thermal imager 132 above or below the multi-spectral walkway 131 can capture thermal images of the gait footprint of the elderly 130, but the multi-spectral thermal imager 132 below can also capture In addition to the thermal image of the 130 gait footprint of the old man, a near-infrared image with clearer contrast of the 130 gait footprint of the old man can be captured.

As shown in Fig. 13A, in order to prevent the elderly 130 from accidentally falling, the multi-spectral walkway 131 may adopt a safety concave walkway 131A, and supporting soft pads 1310 are attached to both sides of the safety concave walkway 131A.

In this embodiment, the method for analyzing gait footprints involves approximately two parameters, including the time/space parameters of the gait footprint and the temperature parameter of the gait footprint.

Among them, the time/space parameters of gait include: walking speed per second along the direction of travel, frequency of steps taken per minute, from the first contact of one foot to the first contact of the opposite foot The elapsed time and the elapsed time from the first contact of one foot to the second contact of the same foot, the swing period of the observed foot off the ground in the gait cycle... etc.

Among them, the temperature parameters of the gait include: the temperature of the two heels in the traveling direction when the heel touches the ground when the heel touches the ground to another (or the same) heel touches the ground when walking, and so on.

The reason why the multi-spectral thermal imaging camera in this case can be applied to the analysis of "gait footprints" provides information about the time/spatial parameters of gait footprints and their temperature parameters. It is mainly based on the fact that the multi-spectral thermal imaging camera can capture and display at the same time. "The above information.

As shown in Figure 13B, the thermal image 1301 of the foot prints left by the elderly 130 when testing on the aisle 131. This thermal image 1301 disappears after about 1 to 3 minutes. The temperature of the feet and feet are tracked and Analysis of changes in the elderly 130, according to foreign medical literature reports on thermal imaging: It can predict the health status of the elderly 130 diseases.

As shown in Figure 13C, the visible light image of the feet and footprints recorded by the old man 130 during the test on the walkway 131. In addition to analyzing the "deformation" of the corresponding pressure, it can also calculate the gait parameters: Data such as stride length and stride time, distance, speed and rhythm.

As shown in Figure 13D, it is a thermal image 1302 of the temperature of the left foot print left by the old man 130 on the aisle 131. From the thermal image 1302, the temperature change information of the left and right feet can be analyzed when they touch off the ground.

Generally, clinical gait abnormality analysis is usually performed for healthy elderly and elderly people with diseases. The above examples are mainly for elderly people with diseases (for example: elderly people with Alzheimer's disease or frailty), so only " Shorter multi-spectral walkway 131 to test. In contrast, healthy elderly people may need a "longer" multi-spectral walkway 131 for testing. At this time, in order to capture more footprint image data, a multi-spectral thermal imaging camera 132 needs to be installed under the walkway 131. The tracking imaging device may be more economical than installing multiple multi-spectral thermal imaging cameras 132.

Please refer to Figure 13E for a schematic diagram of the tracking image capture device.

In another embodiment, as shown in Figure 13E, when the old man 130 is testing on the long walkway 131, a tracking image capturing device 131B that tracks the footprints of the old man 130 can be set up under the walkway 131 as appropriate. Instead of" the implementation in which more than one multi-spectral thermal imaging camera 132 is arranged under the aisle 131.

As shown in Fig. 13E, a tracking image capturing device 131B is installed under the aisle 131 to track the footprints of the elderly 130. Wherein, the tracking image capturing device 131B includes a movable box body 131B1. A multi-spectral thermal imager 132 is arranged on the box body 131B1. Take the image of the footprints on the walkway 131.

Among them, the box 131B1 is set on a ball screw 131B2, which can be moved on the ball screw 131B2 (electrically or manually by a DC motor), so that the multi-spectral thermal imaging camera 132 can move on the aisle 131. "'S footprints.

Wherein, since the mechanical structure of the box body 131B1 of the tracking image capturing device 131B that slides on a ball screw 131B2 is a conventional technology, it will not be described in detail.

Among them, if the box 131B1 moving on the ball screw 131B2 is automatically tracked by a DC motor, it will be supplemented by a photoelectric sensor (Light Sensor) emitting light signal to receive the "reflected" when it touches the foot This signal is used to sense the "movement" signal of the footprint and then instruct the drive motor to rotate correspondingly according to the signal to drive the "movement" position of the multi-spectral thermal imaging camera 132.

Among them, since the sensing method of this photoelectric sensor is also a conventional technology, it will not be described in detail.

As can be seen from the diagrams and descriptions from Figure 9 to Figure 12E above: the multi-spectral image captured by the multi-spectral thermal imager 132 in this case is captured by the first lens of the multi-spectral thermal imager 132 in Figure 9 takes 8 ~ 14 u m far infrared FIR; 0.4 ~ 0.7 u m of the second lens captured visible light VIS, 0.94 u m of the near infrared.

Among them, in the above-mentioned multi-spectral image, an alpha multi-spectral image is formed after the image processing Alpha blending of transparency blending.

Among them, the alpha multispectral image is the transparency blending of "VIS+FIR"; and/or the transparency blending including "VIS+NIR940+FIR", as shown in Figure 9.

Obviously, the alpha multispectral image in this case is different from the MXL technology of FLIR, the largest international thermal imager manufacturer, and FLUKE, the largest international thermal imager manufacturer, using the "RGB + grayscale + thermal image" mixing method.

As mentioned above, the method of capturing the image of the foot print gait analysis, in addition to the corresponding computer APP software program, automatically assists in the analysis of many parameters, including the strength of the foot, the duration of the stopped stance phase and the duration of the mental stress phase And so on important data analysis.

In summary, the patentability of this case is explained as follows:

(1) This case is groundbreaking.

According to the investigation, the current patent documents and related international medical exhibitions show that: (1A). The footprint image (visible light) above the footpath is captured by a visible light camera under the footprint analysis of his gait, so the footpath must be " "Transparent" material, otherwise, the visible light camera will take pictures without code; (1B). If it is a "transparent" trail, then people on this trail will "intentionally or unintentionally watch the situation underneath this trail" In this way, people on this trail will be "distracted", which will affect the reliability of the detection data!

It is worth noting that the technical feature of the trail 131 in this case is "opaque." Obviously, it can solve the problem of "distraction" mentioned above; moreover, the "footprints" can be captured on this opaque trail 131. Image of temperature distribution!

Obviously, this method of detecting and capturing "footprints" images is groundbreaking.

(2) This case is not obvious.

(2A). Among them, this imaging device provides the physiological characteristic images of gait analysis and plantar temperature changes, which can be displayed on the monitoring screen of the same thermal imager at the same time, including thermal images of gait footprints. , Visible light and near-infrared multi-spectral images, reducing the traditional need to use multiple imaging devices to "switch the photographic action and switching components" time, and have the "fast, clear and perspective" function of observation and testing.

(2B). This case can display three wavebands of "thermal image, visible light image + near infrared image" on its liquid crystal display (LCD) 5A6 (as shown in Figure 9A) at the same time. The identified multi-spectral image can be further applied to build a large amount of experimental data database model.

Among them, the “fast, clear and see-through” function in this case means that the images captured by the dual lenses of the multi-spectral thermal imager 5A in this case (such as 5A1 and 5A2 in Figure 9) can be captured at one time at the same time. Its liquid crystal display 5A6 (as shown in Figure 9A) displays three-band recognition images of "8~14um thermal image, 0.4~0.7um visible light image + 0.94um near infrared image", such as in a completely dark environment ( As shown in Figure 1 C of the scheme of this case, it is used to reduce the time of traditional switching screen display:

Among them, the "clear" in this case has the function of "fast, clear and see-through" means that the "0.94um near infrared image" captured by the multi-spectral thermal imager 5A in this case relatively shows the physical image, as shown in the diagram of this case Shown in Figure 1 C.

Among them, "0.94um of near-infrared image" means that 0.94um of near-infrared is irradiated to the foot prints of the elderly, and the "different absorption or reflection of tissues at different positions of the foot" presents near-infrared images with different apparent contrasts.

Among them, the 0.94um emitted by the near-infrared auxiliary light source 5C of the multi-spectral thermal imaging camera 5A in this case is "completely invisible" near-infrared, which is suitable as an artificial "walk" as shown in Figure 13.

And, the “perspective” in the “fast, clear and see-through” function in this case means that the multi-spectral thermal imaging camera 5A in this case can resist the obstacle 5D formed by the “near-permeable material” in an environment with near-infrared. Perform penetration imaging, for example: Figure 1C is in an environment with "enough" near infrared.

Among them, the near-infrared image of the feet of the elderly 130 is captured by the near-infrared auxiliary light source 5C, which radiates a near-infrared 5C111 with a near-infrared wavelength of 0.94um to the soles of the feet, and produces different near-infrared absorption or reflections to different tissues on the body surface. Later, the near-infrared images with different contrasts were clearly displayed. For example, Wien's displacement law shows that the "absorption" or "reflection" produced by different tissues on the body surface of the old man’s 130 feet is about to fall on This near infrared.

In particular, the "see-through" function of the multi-spectral thermal imager 5A in this case is a function that is currently not available in common thermal imagers in various countries!

(3) This case was not affected by the common thermal imaging cameras and the "Teach", "Suggest" and "Motivatuon" principles of No. I 666935, No. I 425292, etc.

(Three A). Explanation about "Teach":

According to the spectrogram captured in Fig. 2; as in Fig. 4 disclosed in No. I 666935 and the prior art, common thermal imaging cameras have removed the "near infrared passable" ICF. Obviously, it is impossible. There is a "teaching" multi-spectral thermal imaging camera 5A so that it can achieve "recommendations" with "fast, clear, and perspective" recognition functions;

(3B). The global large and small factories of the aforementioned common thermal imaging cameras have been dedicated to improving the new technology of the integration of "thermal imaging and visible light" since years of new product launches and merchandise exhibitions, and there is no sign of "teaching" The multi-spectral thermal imaging camera 5A is the "motivation" for the above-mentioned modified structure.

According to the "Near infrared capable of passing 0.7~1.0uM" as disclosed by the second lens of No. I 666935; for this case, as shown in Figure 13, there is still red light for the elderly 130 walking on the opaque walkway 131. The existence of, makes it easy for the elderly 130 to look at them easily, which affects the test results;

And according to the "switching action and switching element" disclosed in No. I 425292, there is no sign of "teaching" the multi-spectral thermal imager 5A to "stick the V940 filter" to modify the structure of the "motivation."

(Three C). In fact, cases such as No. I 666935 and No. I 425292 are not only invention patent cases developed by the inventors, but also the inventor’s team through many experiments to try various possibilities A reasonable combination of, the final degree of improvement has surpassed the use of previous technology components. It is the original common thermal imaging camera, the I 666935 case and the I 425292 case, etc. This technology category is at your fingertips!

Based on the detailed analysis of (1)~(3) above, it can be seen that this case has not been subjected to the "teaching" or "recommendation" of common thermal imaging cameras and prior art such as No. I 666935 and No. I 425292 to achieve this. The principle of the process of innovation "motivation".

1, 2: Glass cup 11: Cold water 3: Inverted opaque black cup 30B2: Pattern 31: Near-infrared flashlight 311: Outline 3111: Object 312, 1301: Thermal image 39: Transparent glass sheet 4: Ceramic cup 41: Color Landscape pattern 30A, 30B1, 411, 412: Thermal image 42: Handle 421: Handle thermal image 20: Dual filter set 22a: Moving plate 5A: Thermal imager, multi-spectral thermal imager 5A1: First lens module, second One lens 5A2: second lens module, second lens 5A21: filter 5A3: body 5A31: focal plane array (FPA) 5A32: thermal image sensor 5A33: circuit control 5A34: image fusion device 5A4: lens frame 5A41 : Distance sensor 5A5: Video button 5A6: Liquid crystal display (LCD) 5A7: Input port 5B: Object 5C: Near-infrared auxiliary light source 5C1: Active frame 5C11: Near-infrared light-emitting diode 5C111: Near-infrared light 5C12: Diffusion Plate 5C2: Fixed frame 5C21: Screw hole 31: Near-infrared flashlight 5D: Obstruction 50: Handheld thermal imager 71: Small animal experiment box S90~S96: Step 111: VIS image 112: FIR thermal image 113, 116 : α multispectral thermal image 114: VIS image 115: FIR thermal image 130: tested elderly, elderly 1301, 1302: thermal image 131: multispectral walkway, test walkway 131B: tracking imaging device 131B1: box 131B2: ball Screw 1310: Soft cushion 131A: Safety concave walkway 1311: Material 132: Multispectral thermal imaging camera

Picture 1 is an example of a real-world target photo

Figure 1A is a thermal image of a target captured by a common thermal imager. Figure 1

Figure 1B is a thermal image of the target captured by a common thermal imager. Figure 2

Figure 1C is a schematic diagram of the thermal image of the target object captured by the multi-spectral thermal imager in this case and

Figure 1D is a schematic diagram of the thermal image of the target object captured by the multi-spectral thermal imager in this case.

Figure 2 is a schematic diagram of the spectrum captured by a common thermal imaging camera

Figure 2A is a schematic diagram of the spectrum captured by the thermal imager I 666935

Figure 2B is a schematic diagram of the spectrum captured by the thermal imager No. I 425292

Figure 2C is a schematic diagram of the spectrum captured by the multispectral thermal imaging camera in this case

Figure 3 shows the thermal image captured by a common thermal imager

Figure 3 A thermal image captured by a multi-spectral thermal imaging camera.

Figure 4 is a schematic diagram of the FLIR thermal imaging camera factory solution

Figure 4A is a schematic diagram of the FLUKE thermal imaging camera factory solution

Figure 5 is a schematic diagram of common thermal imaging cameras, thermal imaging cameras I 666935, thermal imaging cameras I 425292, etc.

Figure 6 is a schematic diagram of the dual-lens imaging process of a multi-spectral thermal imager

Figure 7 is a schematic diagram of the opaque experimental container

Fig. 7 Schematic diagram 1 of the device of the embodiment of the multi-spectral thermal imager

Figure 7 A schematic diagram 2 of the device of the embodiment of the multi-spectral thermal imager

Figure 8 is a schematic diagram of an embodiment of a multi-spectral thermal imaging camera

Figure 8A is a schematic diagram of the liquid crystal display of a multi-spectral thermal imager

Figure 8B is a schematic diagram of the top of the multispectral thermal imager

Figure 8C is a schematic diagram of the active frame 5C1

Figure 9 is a schematic diagram of the process of A multi-spectral thermal image formation

Figure 10 is a basic schematic diagram of transparency blending in one of the embodiments.

Figure 10A is a basic schematic diagram of transparency blending in one of the embodiments.

Figure 11 is a schematic diagram of the mixing of visible light and thermal image transparency

Figure 11: A is a schematic diagram of insufficient visible light and thermal image transparency blending

Picture 12 is a schematic diagram of a thermal image of an ice of Coca-Cola soda

Figure 12A is a thermal image of a glass beaker filled with ice-cold cola

Figure 12B is a schematic view of the thermal image of the coke bamboo chopsticks in the transparent glass beaker

Figure 12C is a schematic diagram of a visible light image of a person's head

Figure 12D is a schematic diagram of the alpha thermal image of a human head

Figure 12E is a schematic diagram of a thermal image of a person's head

Figure 12D is a schematic diagram of the alpha thermal image of a human head.

Figure 13 is a schematic diagram of an embodiment

Figure 13A is a schematic diagram of a safety concave walkway

Figure 13B is a schematic diagram of the thermal image of the footprint

Figure 13C is a schematic diagram of the near-infrared image of the footprint

Figure 13D is a schematic diagram of gait foot print temperature analysis

Claims (13)

A multi-spectral image analysis system, including: One-step path, which can track and detect the residual or display multi-spectral image of the pedestrian walkway in a multi-spectral thermal imaging camera, the walkway is made of a material that can transmit the wavelength range of 0.94~1.1um; At least two multi-spectral thermal imaging cameras are respectively arranged above and below the trail. Each spectral thermal imaging camera has two photographing lenses and a display. The two photographing lenses include a first lens and a second lens. The first lens captures a thermal image with a wavelength of 8~14um, and the second lens captures a near-infrared image with a wavelength in the range of 940±20nm and a visible light image with a wavelength of 0.4~0.7um. The display shows that the thermal image is included. A multispectral image in which three separate images, such as the image, the near-infrared image, and the visible light image, or/and two of them or/and three of them are mixed with different transparency; and A near-infrared auxiliary light source module, which includes a near-infrared projection IR LEDs and a dimmer. The IR LEDs irradiate the walkway, and the dimmer is used to adjust the strength of the IR LEDs. The multi-spectral image analysis system according to claim 1, wherein the material of the trail is PMMA or PC or hard glass. The multi-spectral image analysis system according to claim 1, wherein soft pads for support are attached to both sides of the trail. The multi-spectral image analysis system according to claim 1, wherein the material of the trail is metal, and the thermal conductivity k value of the metal is 200-450 W/(m*K) at 20-50C. The multi-spectral image analysis system according to claim 1, further comprising a ball screw, wherein the multi-spectral thermal imaging camera located under the walkway is arranged on the ball screw and can move on the ball screw. The multi-spectral image analysis system according to claim 1, wherein the second lens has a lens and a light sensor, and the lens and the light sensor are arranged between the lens and the light sensor to allow visible light and wavelength to be 940± A filter passing through 20nm enables the second lens to simultaneously capture a visible light image with a wavelength of 0.4~0.7um plus a near-infrared image with a wavelength of 0.94um. The multi-spectral image analysis system according to claim 1, wherein the A multi-spectral image refers to: the thermal image captured by the first lens is multiplied by an α value as a background image and the second lens The captured visible light image plus the near-infrared image multiplied by an α value is used as a foreground image, and then the foreground image is superimposed on the background image. The multi-spectral image analysis system according to claim 1, wherein the α value is 0 to 1 or between 0% and 100%. A multi-spectral image analysis method, including: (1) Provide a one-step path, which is wide enough for at least one person to walk, and its material is made of a material that can transmit the wavelength range of 0.94~1.1um; (2). Provide at least two multi-spectral thermal imaging cameras, the two multi-spectral thermal imaging cameras are set on the multi-spectral thermal imaging cameras Above and below the trail, the multi-spectral thermal imager includes a first lens and a second lens, wherein the first lens captures a thermal image with a wavelength of 8-14um and the second lens captures a wavelength of 0.4~0.7um visible light image plus near-infrared image with wavelength of 940±20nm; (3) Provide a near-infrared auxiliary light source module, wherein the near-infrared auxiliary light source module includes a near-infrared light source composed of IR LEDs with a radiation wavelength of 940±20nm and a near-infrared light source capable of adjusting the intensity of the IR LEDs. Light modulator; (4) Start the multi-spectral thermal imaging camera and the near-infrared light source; (5) Using the multi-spectral thermal imaging camera to capture a thermal image and a near-infrared image of the footprints left when a person walks on the trail; (6). Form an alpha multi-spectral image with a mixed transparency of the multi-spectral image; Wherein, (6) includes: (6-1). The thermal image captured by the first lens of the multi-spectral thermal imager is used as a background image and the visible light image captured by the second lens is added The above near-infrared image is used as the foreground image, (6-2). The foreground image is superimposed on the background image, and after the transparency mixing process, an alpha multi-spectral thermal image is generated. The method for a multi-spectral image analysis system according to claim 9, wherein the material of the trail is PMMA or PC or hard glass. The method of a multi-spectral image analysis system according to claim 9, wherein in (3) the near-infrared auxiliary light source module is attached to the first lens of the multi-spectral thermal imager arranged below the walkway With that second lens around. The method of a multi-spectral image analysis system according to claim 9, wherein in (6-1), the thermal image captured by the first lens is multiplied by an α value as the background image and the first lens The visible light image captured by the two lenses plus the near-infrared image multiplied by an α value is used as a foreground image, and finally the foreground image is superimposed on the background image. The method of a multi-spectral image analysis system according to claim 12, wherein the α value is 0 to 1 or between 0% and 100%.

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