GB2470741A - Liquid level detection method - Google Patents
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- GB2470741A GB2470741A GB0909480A GB0909480A GB2470741A GB 2470741 A GB2470741 A GB 2470741A GB 0909480 A GB0909480 A GB 0909480A GB 0909480 A GB0909480 A GB 0909480A GB 2470741 A GB2470741 A GB 2470741A
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- 239000007788 liquid Substances 0.000 title claims abstract description 120
- 238000001514 detection method Methods 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 claims abstract description 10
- 230000003287 optical effect Effects 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims description 43
- 238000003708 edge detection Methods 0.000 claims description 10
- 230000009466 transformation Effects 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 2
- 230000001131 transforming effect Effects 0.000 claims description 2
- 230000010354 integration Effects 0.000 claims 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 abstract description 9
- 230000000007 visual effect Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 230000015556 catabolic process Effects 0.000 description 2
- 238000006731 degradation reaction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 239000003643 water by type Substances 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000001990 intravenous administration Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000002604 ultrasonography Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C13/00—Surveying specially adapted to open water, e.g. sea, lake, river or canal
- G01C13/008—Surveying specially adapted to open water, e.g. sea, lake, river or canal measuring depth of open water
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- G01F23/0061—
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/04—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by dip members, e.g. dip-sticks
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/22—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water
- G01F23/28—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water by measuring the variations of parameters of electromagnetic or acoustic waves applied directly to the liquid or fluent solid material
- G01F23/284—Electromagnetic waves
- G01F23/292—Light, e.g. infrared or ultraviolet
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/80—Arrangements for signal processing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/80—Arrangements for signal processing
- G01F23/802—Particular electronic circuits for digital processing equipment
- G01F23/804—Particular electronic circuits for digital processing equipment containing circuits handling parameters other than liquid level
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Fluid Mechanics (AREA)
- Radar, Positioning & Navigation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Hydrology & Water Resources (AREA)
- Signal Processing (AREA)
- Remote Sensing (AREA)
- Electromagnetism (AREA)
- Thermal Sciences (AREA)
- Measurement Of Levels Of Liquids Or Fluent Solid Materials (AREA)
- Image Processing (AREA)
Abstract
A liquid level detection method which may be used todetect water level in a river or reservoir, for example, may also be used to measure liquid level in a container. The method includes capturing an image of a liquid surface 2, a structural surface 3, and graduation markings 5 provided on the structural surface 3 using an image-capturing device 1 to thereby obtain an initial image (31). Subsequently, the initial image (31) is processed so as to generate a processed image (36) , and a level reference value of the liquid surface (2) is obtained from the processed image (36) . The level reference value represents a height of the liquid surface 2 in terms of inherent characteristics of the processed image (36) . Lastly, a liquid level of the liquid surface (2) is calculated based on a relative proportional relation among the level reference value, an overall height of the processed image (36) in terms of the inherent characteristics of the processed image (36) and dimensions of any one of the initial and processed images (31, 36) relative to the graduation markings 5. An angle between an optical axis of the lens 11 and the liquid surface is calculated and the liquid level is corrected based on the angle.
Description
LIQUID LEVEL DETECTION METHOD
The present invention relates to a liquid level detection method.
Determining liquid levels in containers and in outside environments is an activity that is frequently performed. For example, chemistryexperiments regularly involve mixing liquid chemicals in varying amounts.
Accuracy in measuring the amounts of such liquid chemicals is extremely important. As another example, in a medical setting, it may be necessary to determine whether the liquid level in an intravenous container has reached a threshold line and needs refill or replacement. As to measuring liquid levels in outside environments, a common example is that related to determining the water level in a river or reservoir for flood control. That is, it may be necessary to determine the water level in a river or reservoir to facilitate flood control management.
There are two main techniques that are employed to determine liquid levels. One such technique involves visual observation, such as comparing the level of a liquidtograduationmarkings onatest tube, orcomparing the level of water in a river to water level markings on a column of a bridge. The other technique involves theuseofwaterlevelmetersthatemploybuoys, pressure, or ultrasound.
However, there are several disadvantages to such conventional techniques in determining liquid levels as follows: 1. Visual observation is often inaccurate as a result of human error and inexperience. Furthermore, when measurements are conducted outside, it is inconvenient and may even be dangerous to dispatch personnel to flood-prone areas during a storm, typhoon, etc. 2. With respect to conventional equipment used outdoors to automatically detect water levels, installation and calibration of such equipment, which may be quite large, are not easy.
3. The conventional equipment used in outdoor settingsistypicallyplacedincontactwithwater. This not only leads to slow degradation of the equipment due to such constant contact with water, in flooding situations, the equipmentmayevenbedamagedasa result of being subjected to the forces generated by fast-flowing waters.
Therefore, the object of the present invention is toprovidea liquid level detectionmethod that operates based on image-processing techniques.
According to this invention, the liquid level detection method comprises capturing an image of a liquid surface, a structural surface, and graduation markings provided on the structural surface using an image-capturing device to thereby obtain an initial image. Subsequently, the initial image is processed so as to generate a processed image, and a level reference value of the liquid surface is obtained from the processed image. The level reference value represents a height of the liquid surface in terms of inherent characteristics of theprocessedimage. Lastly, a liquid level of the liquid surface is calculated based on a relative proportional relation among the level referencevalue, an overallheight of the processed image in termsof the inherent characteristics of theprocessed image, and dimensions of any one of the initial and processed images relative to the graduation markings.
Other features and advantages of the present invention will become apparent in the following detailed description of the preferred embodiment with reference to the accompanying drawings, of which: Fig. 1 is a flowchart of a liquid level detection method according to a preferred embodiment of the present invention; Fig. 2isaschematicdiagram, illustratinganexample setting in which the liquid detection method of the preferred embodiment may be applied; Fig. 3 is an initial image obtained by an image-capturing device, and which is to be processed in accordance with the liquid detection method of the preferred embodiment; Fig. 4 is a noise-removed image to be processed which is obtained from the initial image according to the liquid detection method of the preferred embodiment; Fig. 5 is a grayscale image obtained from the noise-removed image according to the liquid detection method of the preferred embodiment; Fig. 6 is a binarized image obtained from the grayscale image according to the preferred embodiment; Fig. 7 is an edge-detected image obtained from the binarized image according to the liquid detection method of the preferred embodiment; Fig. 8 is a processed image obtained from the edge-detected image according to the liquid detection method of the preferred embodiment; Fig. 9 shows the processed image, indicatingvarious parameters that are pre-defined, or obtained through the liquid detection method of the preferred embodiment to calculate a liquid level; Fig. 10 is a schematic circuit block diagram of a liquid level detection system according to a preferred embodiment of the present invention; and Fig 11 is a schematic circuit block diagram of components of an image-processing unit in the liquid level detection system of the preferred embodiment.
In the following description, a liquid level
detection method and system according to a preferred embodiment of the present invention are described as being used to detect the water level in a river or reservoir. However, this is merely an example of an V 5 application of the present invention, and the liquid level detection method and system of the present invention may also be used to measure the liquid level in a container, such as a test tube or beaker utilized in a laboratory setting.
The liquid level detection method according to the preferred embodiment of the present invention will now be described with reference to Figs. 1 and 2.
First, in step 41, an image-capturing device 1 having a lens 11 is used to capture an image of a liquid surface 2, a vertically extending structural surface 3 intersecting the liquid surface 2, and graduation markings 5 provided on the structural surface 3 to thereby obtain an initial image 31, as shown in Fig. 3.
It is to be noted that, in this embodiment, capture of the initial image 31 is conducted through a CCD (charge-coupled device) camera (i.e., the image-capturingdevice 1 isaCCD camera). Aconventional CCDcamera usuallyemploys an interleaving scan. In such a camera, all horizontal scan lines are divided into an odd number region and an even number region according to the positions of the rows, and the odd number region and even number region are alternatingly scanned so as to form an entire frame. As a result, object shifting may occur, and to solve this problem, interpolation is often used. However, significant processing time by a processorisinvolvedwithsuchanoperation. Therefore, inthisembodiment, anAXIS�videoserverembeddedsystem is used to convert analog image signals into digital image signals, so as toeffectively increase processing speed. The image resolution may be either 704x480 or 320x240, and the image may be in a Motion JPEG (Joint Photographic Experts Group) digital image format. Hence, in the preferred embodiment, the captured initial image 31 is in a digital signal format.
Next, in step 42, the initial image 31 is processed so as to generate a processed image 36 (see Fig. 8), and a level reference value of the liquid surface 2 is obtainedfrorntheprocessedimage36. Inthisembodirnent, the level reference value represents a height of the liquid surface 2 in terms of inherent characteristics of the processed image 36. An example of such inherent characteristics is provided hereinafter.
As shown in Fig. 1, step 42 includes a plurality of sub-steps as outlined below.
In sub.-step 421, noise removal processing is performedwithrespecttotheinitialimage3ltothereby obtain anoise-removed image tobe processed 32, as shown in Fig. 4. In this embodiment, the noise removal processinginvolvesperformingintegrationwithrespect to the initial image 31 using a smooth filter so as to remove noise by a smoothing effect, thereby reducing the effect of errors caused by subsequent image processing.
Next, in sub-step 422, grayscale transformation processing is performed with respect to the noise-removed image to be processed 32 to thereby obtain a grayscale image 33, as shown in Fig. 5. In this embodiment, the grayscale transformation processing involves transforming the noise-removed image to be processed 32 into an image in a grayscale format to thereby obtain the grayscale image 33. Grayscale transformation processing is performed due to the large data sizes associated with color images.
Next, in sub-step 423, binarization processing is performed with respect to the grayscale image 33 so as to obtain a binarized image 34, as shown in Fig. 6. The binarized image 34 allows for higher processing efficiencyandoccupieslessmemoryspace. Furthermore, the image resulting from binarization processing (the binarized image 34 in this example) allows for better distinguishing between an object (s) and the background in such an image.
In this embodiment, the binarization processing involves setting each pixel in the grayscale image 33 that has a pixel value lower than a threshold value to a first color, and setting each pixel in the grayscale image 33 that has a pixel value not lower than the threshold value to a second color. In this embodiment, as shown in Fig. 6, the first color is black and the second color is white. Furthermore, in this embodiment, * 8 before generation of the binarized image 34, histogram frequencydistributionprocessing is conducted, so that, during the binarization processing, the problem of differences in color levels caused by the influence of the environment, the picture-taking angle, and illumination during image capturing may be alleviated.
Next, in sub-step 424, edge detection processing is performed with respect to the binarized image 34 so as to obtain an edge-detected image 35, as shown in Fig. 7. The main purpose of edge detection processing is to find the boundaries between the object(s) and the background in an image. Most edge detection involves using differences in grayscale values of adjacent pixels man image todetectedges. Ifadifference ingrayscale values is large, then this indicates the presence of an edge, otherwise it may be determined that there is no edge present. However, in many instances, the edges are not formed by single pixels, and instead, may be formed by groups of pixels and the actual edge is present thereamong. This increases the difficulty in edge detection. Moreover, noise is another factor, which is generated randomly and therefore hard to predict. For these reasons, in this embodiment, edge detection processing involves useof aderivative filter to sharpen the binarized image 34.
In the next step, making use of the fact that the liquid surface 2 forms approximately a straight line, straight line detection is performed to find areas that maypotentiallybe the liquid surface 2, and the remaining noise of surplus line segments that are unable to form straight lines is removed. In particular, in sub-step 425, straight line detection processing is performed with respect to the edge-detected image 35 so as to obtain the processed image 36 and a liquid surface line, which isindicatedbythearrowinFig. 8, andtheliquidsurface line is converted into the level reference value, which is indicated as 75 pixels in Fig. 9. The level reference value is described in greater detail below.
The straight line detection processing involves removing noise of surplus line segments that do not form a straight line in the edge-detected image 35. Moreover, in this embodiment, the straight line detection processing involves utilization of the Hough transform technique to remove the noise of surplus line segments that do not form a straight line in the edge-detected image 35.
In the Hough transform technique, a straight line in an x-y coordinate plane is transformed into a point in a theta-rho coordinate plane, in which theta is the slope of the straight line in the x-y coordinate plane, and rho is the intercept of the straight line in the x-y coordinate plane. As an example, the two straight lines ylmx+b and y2=ax+c in the x-y coordinate plane may be converted into two points (m, b) and (a, c) in the theta-rho coordinate plane. After Hough transformation, a large number of line segments will intersect to a point or form peaks at a vicinity thereof due to having the same slope and similar intercepts.
As a result, a peak value derived by the Hough transform technique may be used to find the straight lines in the binarized image 34.
Next, instep 43, a liquid level of the liquid surface 2 is calculated based on a relative proportional relation among the level reference value, an overall height of the processed image 36 in terms of the inherent characteristics of the processed image 36, and dimensions of any one of the initial and processed images 31, 36 relative to the graduation markings 5.
In this embodiment, the overall height of the processed image 36 is a number of pixels along a vertical line between upper and lower boundaries of the processed image 36, and the level reference value is a number of pixels along the vertical line from the lower boundary of the processed image 36 to a representation of the liquid surface in the processed image 36 (i.e., to the liquid surface line) Furthermore, in this embodiment, the dimensions of any one of the initial and processed images 31, 36 relative to the graduation markings 5 are given values, andarevaluesofthegraduationmarkings5corresponding respectively to the upper and lower boundaries of any one of the initial and processed images 31, 36. For example, an image may be captured in a low water state (or when a container is empty) , and the graduation markings 5 corresponding to upper and lower boundaries of such an image may be obtained by visual observation.
Since the upper and lower boundaries do not change, the values thus obtained are the same as the values of the graduation markings 5 corresponding to the upper and lower boundaries of any one of the initial and processed images 31, 36.
According to one embodiment, in step 43, the relative proportional relation used to calculate the liquid level of the liquid surface 2 involves interpolation using the level reference value, the overall height of the processed image 36, and the dimensions of any one of the initial and processed images 31, 36 relative to the graduation markings 5. For example, in this embodiment, the liquid level of the liquid surface 2 is calculated according to the following formula: x + a (y -where (x) is the value of the graduation marking 5 corresponding to the lower boundary of any one of the initial and processed images 31, 36, (y) is the value of the graduation marking 5 corresponding to the upper boundary of any one of the initial and processed images 31, 36, and (a) is a ratio of the level reference value to the overall height of the processed image 36.
Referring to Fig. 9, assuming a value of 164.5 meters for the graduation marking 5 corresponding to the lower boundary of the processed image 36, a value of 169.5 meters for the graduation marking 5 corresponding to the upper boundary of the processed image 36, a value of 75 pixels for the level reference value, and a value of 240 pixels for the overall height of the processed image 36, the liquid level of the liquid surface 2 may be calculated using the above formula as follows: 164.5 + 75/240 (169.5 -164.5) = 166.06 meters Lastly, in step 44, an angle between an optical axis of the lens 11 of the image-capturing device 1 and the liquid surface 2 is calculated, and the liquid level of the liquid surface 2 calculated in step 43 is corrected based on the angle. In this embodiment, the correction of the liquid level is performed using a trigonometric function with respect to the angle between the optical axis of the lens 11 of the image-capturing device 1 and the liquid surface 2.
Referring to Fig. 10, the liquid level detection system 100 according to a preferred embodiment of the present invention comprises the image-capturing device lhavingthe lens 11, animage-processingunitliOcoupled to the image-capturing device 1, a liquid level-calculating unit 120 coupled to the image-processing unit 110, anda level-correcting unit coupled to the liquid level-calculating unit 120. * 13
The image-capturing device 1 captures an image of the liquid surface 2, the vertically extending structural surface 3 intersecting the liquid surface 2, and the graduation markings 5 provided on the structural surface 3 to thereby obtain the initial image 31, as shown in Fig. 3.
The image-processing unit 110 processes the initial image 31 so as to generate the processed image 36, as shown in Fig. 8, and obtains th.e level reference value of the liquid surface 2 from the processed image 36.
The liquid level-calculating unit 120 calculates the liquid level of the liquid surface 2 based on the relative proportional relation among the level reference value, the overall height of the processed image 36 in terms of inherent characteristics of the processed image 36, and dimensions of any one of the initial and processed images 31, 36 relative to the graduation markings 5.
The level-correcting unit 130 calculates the angle between the optical axis of the lens 11 of the image-capturing device 1 and the liquid surface 2, and corrects the liquid level of the liquid surface 2 calculated by the liquid level-calculating unit 120 based on the angle.
In some embodiments, with reference to Fig. 11, a computer may be configured with proprietary software to result in the liquid level-calculating unit 120, the level-correcting unit 130, and the image-processing unit llOhavingthefollowingcomponents: anoise removal processor 111 coupled to the image-capturing device 1 and forperformingnoise removal processingwith respect to the initial image 31 to thereby obtain the noise-removed image to be processed 32; a grayscale transformation processor 112 coupled to the noise removal processor 111 and for performing grayscale transformation processing with respect to the noise-removed image to be processed 32 to thereby obtain the grayscale image 33; a binarization processor 113 coupled to the grayscale transformation processor 112 for performing binarization processing with respect to the grayscale image 33 so as to obtain the binarized image 34; an edge detection processor 114 coupled to the binarization processor 113 and for performing edge detection processing with respect to the binarized image 34 so as to obtain the edge-detected image 35; and a straight line detection processor 115 coupled to the edge detection processor 114 and for performing straight line detection processing with respect to the edge-detected image 35 so as to obtain the processed image 36 and the liquid surface line. The straight line detectionprocessor 115 also converts the liquid surface line into the level reference value.
The liquid level detection method and system according to present invention have the following advantages: 1. Since the liquid level is calculated on the basis of a captured image and is not determined by visual observation, inaccuracies caused by human error and inexperience are avoided.
2. The only equipment that must be placed at the measurement site for the liquid level detection method and system of the present invention is the image-capturing device 1. Furthermore, the initial image 31 captured by the image-capturing device 1 may be obtained by the image-processing unit 110 via a wireless network. Finally, the image-capturing device 1 need not be made to any particular specification, and in fact, manycommerciallyavailable camerasmaybe used.
Hence, minimal installation and calibration, as well as high mobility are associated with the present invention.
3. Through use of images captured by the image-capturing device 1, there need not be any direct contact with the liquid being measured. Hence, there is no danger of degradation of equipment resulting from constantcontactwithliquids, norofdamagetoequipment as a result of being subjected to forces generated by fast-flowing waters.
4. As a result of the processing performed in order to obtain the processed image 36 (i.e., the sub-steps of step 42) , the complexity in calculating the level of the liquid surface 2 is reduced. Additionally, this allows for quick and accurate searching of information related to the processed image 36 after such information is stored in a database. * 17
Claims (18)
- Claims: 1. A liquid level detection method comprising: (a) capturing an image of a liquid surface, a structural surface, and graduation markings provided on the structural surface using an image-capturing device to thereby obtain an initial image; (b) processing the initial image so as to generate aprocessed image, and obtaininga level reference value of the liquid surface fromtheprocessed image, the level reference value representing a height of the liquid surface in terms of inherent characteristics of the processed image; and (c) calculating a liquid level of the liquid surface based on a relative proportional relation among the level referencevalue, anoverall height of theprocessed image interms of the inherent characteristics of theprocessed image, and dimensions of any one of the initial and processed images relative to the graduation markings.
- 2. The liquid level detection method of claim 1, further comprising: Cd) determining an angle between an optical axis of a lens of the image-capturing device and the liquid surface, and correcting the liquid level of the liquid surface calculated in step (c) based on the angle.
- 3. The liquid level detection method of claim 2, wherein, in step (d) , the correction of the liquid level is performed using a trigonometric function with respect to the angle between the optical axis of the lens of the image-capturing device and the liquid surface.
- 4. The liquid level detection method of claim 1, wherein the dimensions of any one of the initial and processed images relative to the graduation markings are given values, and are values of the graduation markings corresponding respectively to upper and lower boundaries of any one of the initial and processed images.
- 5. The liquid level detection method of claim 4, wherein, instep (c), the relativeproportional relation used to calculate the liquid level of the liquid surface involves interpolation using the level reference value, the overall height of the processed image, and the dimensions of any one of the initial and processed images relative to the graduation markings.
- 6. The liquid level detection method of claim 5, wherein the overall height of the processed image is a number of pixels along a vertical line between the upper and lower boundaries of the processed image, and the level reference value is a number of pixels along the vertical line from the lower boundary of the processed image to a representation of the liquid surface in the processed image.
- 7. The liquid level detection method of claim 6, wherein, in step (c), the liquid level of the liquid surface is calculated according to the following formula: * 19 x + a (y -x), where (x) is the value of the graduation marking corresponding to the lower boundary of any one of the initial and processed images, (y) is the value of the graduation marking corresponding to the upper boundary of any one of the initial and processed images, and (a) is a ratio of the level reference value to the overall height of the processed image.
- 8. The liquid level detection method of claim 1, wherein said processing the initial image so as to generate the processed image of step (b) includes: (bi) performing noise removal processing with respect to the initial image so as to obtain a noise-removed image to be processed; (b2) performing grayscale transformation processing with respect to the noise-removed image to be processed so as to obtain a grayscale image; (b3) performing binarization processing with respect to the grayscale image so as to obtain a binarized image; (b4) performing edge detection processing with respect to the binarized image so as to obtain an edge-detected image; and (b5) performing straight line detection processing with respect to the edge-detected image so as to obtain the processed image and a liquid surface line, and converting the liquid surface line into the level reference value. * 20
- 9. The liquid level detection method of claim 8, wherein, in step (bl), the noise removal processing involves performing integration with respect to the initial image using a smooth filter so as to remove noise.
- 10. The liquid level detection method of claim 8, wherein, in step (b2), the grayscale transformation processing involves transforming the noise-removed image to be processed into an image in a grayscale format to obtain the grayscale image.
- 11. The liquid level detection method of claim 8, wherein, in step (b3), the binarization processing involves setting each pixel in the grayscale image that has a pixel value lower than a threshold value to a first color, and setting each pixel iii the grayscale image that has a pixel value not lower than the threshold value to a second color.
- 12. The liquid level detection method of claim 11, wherein, in step (b3) , the first color is black and the second color is white, and before generation of the binarized image, histogram frequency distribution processing is conducted.
- 13. The liquid level detection method of claim 8, wherein, in step (b4), the edge detection processing involves using a derivative filter to sharpen the binarized image.
- 14. The liquid level detection method of claim 8, wherein, in step (b5), the straight line detection processing involves removing noise of surplus line segments that do not form a straight line in the edge-detected image.
- 15. The liquid level detection method of claim 14, wherein, in step (b5), the straight line detection processing involves utilization of the Hough transform technique to remove the noise of surplus line segments that do not form a straight line in the edge-detected image.
- 16. The liquid level detection method of claim 8, wherein the captured initial image is in a digital signal format.
- 17. The liquid level detection method of claim 1, wherein the structural surface is averticallyextending surface that intersects the liquid surface.
- 18. A liquid level detection method as hereinbefore described with reference to and as illustrated in 1 to 11.
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| GB0909480A GB2470741A (en) | 2009-06-02 | 2009-06-02 | Liquid level detection method |
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| GB0909480A GB2470741A (en) | 2009-06-02 | 2009-06-02 | Liquid level detection method |
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| CN110567443A (en) * | 2019-09-03 | 2019-12-13 | 河南省水文水资源局(河南省水资源监测管理中心) | Electronic depth sounding rod |
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| CN114913225B (en) * | 2021-02-10 | 2024-04-09 | 上海梅山钢铁股份有限公司 | Converter liquid level real-time measurement method based on monocular vision |
| CN114877974B (en) * | 2022-06-08 | 2022-12-23 | 广州计量检测技术研究院 | Automatic liquid level setting method, device and equipment of measuring glass measuring device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0798238A (en) * | 1993-09-27 | 1995-04-11 | Kiichi Taga | Water gauge using video camera |
| JP2001133311A (en) * | 1999-11-04 | 2001-05-18 | Hitachi Ltd | Water level measuring method and water level measuring system |
| JP2002031562A (en) * | 2000-07-14 | 2002-01-31 | Toshiba Corp | Water level measuring device, and water level measuring method |
| JP2003149032A (en) * | 2001-11-16 | 2003-05-21 | Mitsubishi Electric Corp | Level measuring device |
| FR2865802A1 (en) * | 2004-01-30 | 2005-08-05 | France Etat Ponts Chaussees | Water level measurement device for e.g. river, has storage and processing circuit processing image taken by camera to provide information representative of liquid level with respect to reference level |
| WO2007032595A1 (en) * | 2005-09-16 | 2007-03-22 | Korea Institute Of Construction Technology | System and method for measuring liquid level by image |
-
2009
- 2009-06-02 GB GB0909480A patent/GB2470741A/en not_active Withdrawn
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0798238A (en) * | 1993-09-27 | 1995-04-11 | Kiichi Taga | Water gauge using video camera |
| JP2001133311A (en) * | 1999-11-04 | 2001-05-18 | Hitachi Ltd | Water level measuring method and water level measuring system |
| JP2002031562A (en) * | 2000-07-14 | 2002-01-31 | Toshiba Corp | Water level measuring device, and water level measuring method |
| JP2003149032A (en) * | 2001-11-16 | 2003-05-21 | Mitsubishi Electric Corp | Level measuring device |
| FR2865802A1 (en) * | 2004-01-30 | 2005-08-05 | France Etat Ponts Chaussees | Water level measurement device for e.g. river, has storage and processing circuit processing image taken by camera to provide information representative of liquid level with respect to reference level |
| WO2007032595A1 (en) * | 2005-09-16 | 2007-03-22 | Korea Institute Of Construction Technology | System and method for measuring liquid level by image |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104950856A (en) * | 2015-06-19 | 2015-09-30 | 华北水利水电大学 | Reservoir dispatching management system considering river ecological demands |
| CN110567443A (en) * | 2019-09-03 | 2019-12-13 | 河南省水文水资源局(河南省水资源监测管理中心) | Electronic depth sounding rod |
Also Published As
| Publication number | Publication date |
|---|---|
| GB0909480D0 (en) | 2009-07-15 |
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