Element position calculation system and element position calculation method

Abstract

To provide an element position calculation system and an element position calculation method that can easily calculate desired position coordinate information as numerical data from image data of a framing plan from which information on numerical values and geometric shape is lost.SOLUTION: An element position calculation system 100 is for calculating position coordinates of elements E, E ... from image data D of a framing plan in which a plurality of elements for construction are described, and comprises: element detection means 1 that detects the positions of the elements E, E ... from the image data D; and coordinate calculation means 3 that calculates the position coordinates of the elements E, E ... from reference dimension information that is an actual dimension and reference position information of a building.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an element position calculation system and an element position calculation method for calculating the position coordinates of each element, such as a pile, required for architectural design from various framing plans created in the design stage of a building. [Background technology]

[0002] During the design stage of a building, various floor plans are created. A floor plan is a plan view showing each element of the structure, such as the foundation, floor, and ceiling, from above. Depending on the elements involved, there are various types of floor plans, such as foundation plans, shed plans, floor plans, and ceiling plans.

[0003] These framing plans include various dimensions, such as the distance between beams and piles. Although the methods and standards for indicating these dimensions are not necessarily uniform, they are generally shown as the relative distance between two points for each element. However, in some cases, it may be more convenient to show the dimensions in terms of cumulative dimensions from a certain reference point, or conversely, it may be more convenient to show the dimensions in terms of relative distances between two points rather than in terms of the dimensions.

[0004] These framing plans are generally created using a two-dimensional CAD (Computer Aided Design) system (hereafter referred to as CAD), and are output as vector data such as PDF (Portable Document Format) data or raster data such as JPEG (Joint Photographic Experts Group).

[0005] When issuing drawings, foundation plans and pile plans are issued to the contractor constructing the foundation, and floor plans and shed plans are issued to the contractor constructing the structure. However, because the CAD systems used by each contractor are not the same, it is often not possible to issue drawings using CAD data. Therefore, the reality is that drawings are exchanged as PDF data, JPEG data, etc., or printed out on a printer or other device as appropriate and exchanged as paper drawings.

[0006] As such, when the framing plans used at each design site are PDF data, JPEG data, paper drawings, etc., the method and standards for indicating dimensions are undesirable, which can cause inconvenience when recalculating dimensions. For example, if you want to calculate the projection dimensions rather than the relative distance between two points, the numerical information in the PDF data, JPEG data, or paper drawings has already been lost as digital data, so a person must read the dimensions by eye, enter them into a calculator or spreadsheet, etc., and recalculate.

[0007] Figure 9 shows an example of a drawing in which the dimensions have been re-written by hand. This type of work not only lengthens the design work time and is inefficient, even for a small, average house, but also leads to calculation errors.

[0008] As a technology for converting image data of drawings into digital data, a construction drawing recognition method has been developed to convert paper drawings into image data, detect wall elements from the proportion of black pixels, and convert them into vector data that can be used in a CAD system (see Patent Document 1). The technology in Patent Document 1 divides image data into rectangular segments along the Cartesian coordinates, and recognizes a wall when there are a large number of black pixels in each rectangular segment. Information about the recognized wall is stored in memory along with information on its position, dimensions, etc., and can be utilized. [Prior art documents] [Patent documents]

[0009] [Patent Document 1] Japanese Patent Application Publication No. 9-128425 Summary of the Invention [Problem to be solved by the invention]

[0010] However, the construction drawing recognition method in Patent Document 1 determines whether or not a drawing is a wall based on the number of black pixels in a narrow, strip-like area, so it cannot detect walls that are arranged diagonally rather than orthogonally, or arc-shaped walls. Similarly, markers such as stakes are arranged as figures and are not elongated figures extending in the orthogonal direction, and therefore cannot be detected by this method.

[0011] Furthermore, since the wall position and dimension information is thought to be in pixel units, even if the output vector data is opened in a CAD system, there is the problem that the scale must be manually changed to match the actual dimensions.

[0012] The present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide an element position calculation system and an element position calculation method that can easily calculate desired position coordinate information as actual-size numerical data from image data of a framing plan in which numerical and geometric shape information has been lost. [Means for solving the problem]

[0013] The means adopted by the present inventors to solve the above problems will be described below. The element position calculation system of the present invention is an element position calculation system for calculating the position coordinates of each element from image data of a floor plan on which a plurality of element markers for construction are written. The basic configuration of the present invention comprises an element detection means for detecting the position of the element marker from the image data, and a coordinate calculation means for calculating the position coordinates of each of the element markers from reference dimension information, which is the actual dimension, and reference position information of the building.

[0014] In this invention, an element refers to each element of a building structure, such as a pile, foundation, floor, wall, ceiling, etc. Furthermore, image data refers to data that can be recognized as a two-dimensional image, and includes either or both of vector data and raster data, from which digital information regarding at least dimensions and geometric shape has been lost.

[0015] In this invention, for multiple elements detected by the element detection means, the position dimensions of the detected elements are converted to actual dimensions using reference dimension information, which is the actual dimensions. Then, by using the reference position information of the building and setting that position as the coordinate origin, the position coordinates of each element can be calculated as actual dimensions. This makes it possible to easily obtain the actual dimensional position coordinates of each element regardless of the scale of the drawing or image data.

[0016] The following means can be used to solve the problem. In the above configuration, it is also possible to configure the element as a pile, and to calculate the position coordinates of each pile from image data of a pile plan showing multiple piles.

[0017] The pile markers shown on a typical pile plan are drawn in various sizes depending on the drafter, but they are often represented by a geometric shape, such as a circle, that allows for a definable center that serves as the pile core, and are unified into the same geometric shape within a single drawing. Focusing on this point, particularly for pile markers in pile elevation drawings, the position coordinates of the pile cores, which are required as position coordinate information, can be detected with high accuracy by the element detection means, regardless of their size.

[0018] In addition, in pile construction drawings, it may be more convenient to use offset dimensions, which are cumulative dimensions from the reference coordinate system, for ease of work during construction. Therefore, for example, the position of the outermost pile is used as the reference position information, and the actual distance between the farthest piles is used as the reference dimension information, and the coordinate calculation means calculates the position coordinates of each of the elements. This allows the position coordinates of the pile core to be calculated in actual dimensions, and the numerical data can be used for construction, etc. Note that the reference dimension information is not limited to information based on the actual dimensions of the furthest piles, but includes information based on the actual dimensions of any piles.

[0019] As yet another means that can be adopted to solve the problem, it is also possible to use an image classification system based on machine learning as the element detection means. There is no standardized method for depicting elements, and it varies depending on the drafter and CAD system. For example, as mentioned above, stake markers are often circle-shaped, but they can also be large or small. They can also be solid or unfilled.

[0020] In order to accurately detect elements that can be depicted in various types, a simple algorithm that detects pixel colors or boundaries would require an enormous number of detection conditions and would therefore be unrealistic. Therefore, by detecting elements using an image classification system that uses machine learning, it is possible to accurately detect markers even if the sizes and types of markers are different. Note that the machine learning in the present invention is not limited to the type such as supervised learning, unsupervised learning, deep learning, etc., and can be selected from various algorithms.

[0021] As still another means that can be employed to solve the problem, it is also possible to further provide an alignment means that is configured to correct the positions of the plurality of elements detected by the element detection means that are arranged in rows within a predetermined error range in each direction of a Cartesian coordinate system on the entire drawing, so that the positions of the plurality of elements are aligned on the reference axis of each row.

[0022] For example, when the vertical and horizontal coordinate axes of a drawing are considered to be an orthogonal coordinate system, and multiple elements are lined up in a vertical row, the vertically lined elements may not be aligned in a single row due to the influence of the detection accuracy of the element detection means, and their horizontal positions may vary slightly.

[0023] Even in this case, if the variation is within a predetermined error range, the horizontal positions of the multiple elements are aligned on a vertical reference axis. There are various methods for determining the reference axis, but one example is an axis that passes through the coordinates of the median values between the multiple elements that are furthest apart in the horizontal direction.

[0024] In this way, when the detected elements are slightly misaligned in a design in which the elements are lined up in a vertical row, the alignment means corrects the design by assuming that the elements should actually be arranged in an orderly manner in a row, since a design with such slightly different dimensions is unnatural. This allows for automatic correction of variations in the accuracy of the detection results of the element detection means by correcting the positions of multiple elements that are arranged in rows within a specified error range so that they are aligned on the reference axis of each row.

[0025] The above configuration may further comprise a rounding means, which may be configured to correct both or either of the plurality of elements detected by the element detection means and the plurality of elements aligned on the reference axis in any direction of the Cartesian coordinate system so as to have predetermined coordinate values.

[0026] In most cases, building elements are arranged according to standard dimensions and intervals. Therefore, detected elements with position coordinates close to those standard dimensions and intervals are corrected to match the predetermined position coordinates, assuming that they were originally those dimensions and intervals. This makes it possible to automatically correct variations in the accuracy of the detection results of the element detection means.

[0027] As yet another means that can be adopted to solve the problem, an element position calculation method for calculating the position coordinates of each element from image data of a floor plan showing multiple architectural elements can be adopted. In this configuration, the method comprises an element detection step of detecting the position of the element from the image data, and a coordinate calculation step of calculating the position coordinates of each element from reference dimension information, which is the actual dimension, and reference position information of the building.

[0028] Even with this configuration, for multiple elements detected in the element detection step, the position dimensions of the detected elements are converted to actual dimensions using reference dimension information, which is the actual dimensions, and the position is set as the coordinate origin using the reference position information of the building, so that the position coordinates of each element can be calculated as actual dimensions.

[0029] In addition, in the above configuration, the elements can be piles, and the element detection step can be configured to use an image classification system using machine learning to calculate the position coordinates of each pile from image data of a pile plan showing multiple piles.

[0030] With the above configuration, the required center position of a pile in a pile plan can be detected with high accuracy in the element detection step, regardless of its size. In addition, by using the position of the outermost pile as the reference position information and the actual distance between the furthest piles as the reference dimension information, the position coordinates of each element can be calculated in the coordinate calculation step. This allows the position coordinates of the pile core to be calculated in actual dimensions, and the numerical data can be used for construction, etc.

[0031] The above configuration may further include an alignment step. The alignment step corrects the positions of the multiple elements detected in the element detection step that are arranged in rows within a predetermined error range in each direction of the Cartesian coordinate system so that the elements are aligned on the reference axis of each row.

[0032] The method may further comprise a rounding step, in which the multiple elements detected by the element detection means and / or the multiple elements aligned on the reference axis are corrected to predetermined coordinate values in any direction of the Cartesian coordinate system.

[0033] By providing such an alignment step and rounding step, for each element detected in the element detection step that is arranged in a row within a predetermined error range, the positions of the multiple elements are corrected so that they are aligned on the reference axis of each row, thereby automatically correcting variations in the accuracy of the detection results in the element detection step.

[0034] Furthermore, since elements in a building are almost always arranged with fixed standard dimensions and spacing, elements detected by the element detection step that have position coordinates close to those standard dimensions and spacing can be automatically corrected to have predetermined position coordinates, assuming that they were originally those dimensions and spacing. [Effects of the Invention]

[0035] In the element position calculation system of the present invention, the coordinate calculation means calculates the position coordinates of each element detected by the element detection means from the reference dimension information, which is the actual dimension, and the reference position information of the building. In the element position calculation method, the coordinate calculation step calculates the position coordinates of each element detected in the element detection step from reference dimension information, which is the actual dimension, and reference position information of the building. This has the effect of making it possible to easily calculate desired position coordinate information as actual dimensional numerical data from image data of a framing plan in which numerical and geometric shape information has been lost. [Brief explanation of the drawings]

[0036] [Figure 1] 1 is an explanatory diagram illustrating a configuration of an element position calculation system according to the present invention. [Figure 2] 1 is a flowchart showing a processing flow of the element position calculation system of the present invention. [Figure 3] FIG. 10 is an explanatory diagram illustrating a state in which a drawing is read in the element position calculation system of the present invention. [Figure 4] 10A and 10B are explanatory diagrams illustrating a state in which elements are detected in the element position calculation system of the present invention. [Figure 5] FIG. 10 is an explanatory diagram showing an aligned state in the element position calculation system of the present invention. [Figure 6] FIG. 10 is an explanatory diagram showing a state in which an ejection dimension is displayed in the element position calculation system of the present invention. [Figure 7] FIG. 10 is an explanatory diagram showing a state where rounding is performed in the element position calculation system of the present invention. [Figure 8] FIG. 10 is an explanatory diagram illustrating an element position calculation system according to a first modified example of the present invention. [Figure 9] This is an example of a framing plan in which the displacement dimensions were calculated manually using conventional methods. DETAILED DESCRIPTION OF THE INVENTION

[0037] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to Figures 1 to 7. In the following description, the figures are shown in a schematic manner for the sake of simplicity. The element position calculation system (hereinafter also simply referred to as the system) 100 of the present invention is a system that operates on the web, as shown in Fig. 1, and a customer terminal C connects to the system 100 via the internet. Although the system shown in Fig. 1 is a web system, it may also be a system that is installed on the customer terminal C and operates as a stand-alone system, and the system's form is not limited thereto.

[0038] A user U is a user of this system 100 and transmits image data D of a framing plan from a customer terminal C to the system 100 . The image data D to be transmitted can be various framing plans, for example, if element E is a pile, it will be a pile framing plan, and if element E is a foundation, it will be a foundation framing plan. In the following figures, we will explain the image data D related to a pile framing plan as an example.

[0039] Image data D is data input to or pre-stored on the customer terminal C, and may be, for example, vector data such as PDF output from a CAD system, or raster data such as JPEG or PNG (Portable Network Graphics) obtained by scanning a paper drawing with a scanner S. In the case of raster data obtained by scanning a paper drawing, the entire data may be tilted, so a tilt correction function may be installed.

[0040] These image data D lose at least the digital information related to dimensions and geometric shapes. In other words, if it is raster data, it is array data for each pixel. Even if it is vector data, the numerical parts are not represented as numerical values, but are represented as a collection of lines. Furthermore, the circular parts are represented as a collection of straight lines and curves, and the information about the mathematical formula for the circle is lost.

[0041] The system 100 is a system stored on a server or cloud, and includes an element detection means 1, an alignment means 2, a coordinate calculation means 3, and a rounding means 4. The alignment means 2 and the rounding means 4 are not essential components, but as will be described later, they are effective means for correcting the influence of the detection accuracy of the element detection means 1. The rounding means 4 may be configured to operate before the operation of the coordinate calculation means 3, or may be configured to operate after the operation of the coordinate calculation means 3.

[0042] First, we will explain the element detection means 1. The element detection means 1 reads image data D sent from the customer terminal C and detects the position of element E. Here, in the pile plan in image data D of Fig. 1, element E is a pile. Stake markers (i.e., markers representing element E) are often depicted as circles, and when the element detection means 1 detects a marker, it displays a center line and a circle of a specified diameter at the position of the marker.

[0043] Although various algorithms can be used to detect this element E, it is preferable to use an image classification system using machine learning. Regarding machine learning, supervised learning is effective, but various learning algorithms such as unsupervised learning can also be used.

[0044] To detect element E, the shape and color of the markers used vary depending on the framing plan. Therefore, for markers that are thought to be element E, the number of markers with the same characteristics is counted, and if that number is relatively greater than the number of markers that are thought to have other characteristics, it is determined to be element E on that framing plan. Conversely, for markers with characteristics that are only detected in one or two places, filtering them out as being mere symbols or letters other than element E makes it possible to reliably detect the required element E. In addition, when detecting element E, it is preferable to configure the system so that markers with geometric shapes such as circles and rectangles that exist outside the range of the foundation part in the framing plan are excluded from detection.

[0045] Next, we will explain the alignment means 2. The alignment means 2 may correct the positions of the elements E·E... arranged in a row when slight variations in each position occur due to detection errors of the element detection means 1, so that the elements E·E... are aligned on the reference axis of each row.

[0046] As an example, if multiple elements E·E... arranged vertically have slight variations in their arrangement in the left-right direction, all elements E·E... can be aligned to the midpoint of the left-right distance between the leftmost element E and the rightmost element E.

[0047] Next, a description will be given of the coordinate calculation means 3. The coordinate calculation means 3 can be composed of, for example, a reference dimension determination means 31 and an extrusion dimension calculation means 32. The reference dimension determination means 31 is a means for determining a reference dimension for converting the spacing between elements E·E... read by the element detection means 1 into actual dimensions, and for example, reads and inputs the dimension of the most distant element E·E among the various dimensions shown in the image data D of the floor plan. The actual dimension value of the read dimension is recorded as reference dimension information. The dimensions may be read visually by the user U, or may be read automatically by image detection. A coefficient is then calculated to match the dimension read in this way with the system distance value of the furthest element E·E. For example, if the number of pixels between the furthest elements E·E is 1000px and the actual dimension read is 10m (10,000mm), the coefficient is 10mm / px.

[0048] The extrusion dimension calculation means 32 calculates the extrusion dimension, which is a cumulative dimension instruction from the reference position, for each detected element E. Any position can be selected as the reference position, but for example, the coordinates of the element E located at the top left can be set as the reference position information. This reference position can be set in advance to be the top left element E, or the user U can manually select and determine any element E.

[0049] Then, the position coordinates of each element E·E... are calculated in actual dimensions using the coefficients calculated from the above-mentioned reference dimension information and the reference position information, to obtain the offset dimensions. The removal dimensions can be displayed on the loaded image data D, and can also be output as csv (Comma Separated Values) data. Although the ejection dimension calculation means 32 calculates the ejection dimension in the above example, it may be configured to calculate the relative distance between two points of each element E·E . . .

[0050] Finally, we will explain the rounding means 4. The rounding means 4 corrects the multiple elements E·E... detected by the element detection means 1 so that they have predetermined coordinate values in any direction of the Cartesian coordinate system. For example, in the case of piles, the traditional Japanese practice is to use 1 ken (6 shaku = approximately 1.82 m) as the standard and place them at intervals of 1 / 2 or an integral multiple of that, or to use 1 m as the standard and place them at intervals of 1 / 2 or an integral multiple of that. Therefore, as an example, if the spacing between piles detected by the element detection means 1 is detected as 1.81 m, the rounding means will correct it to 1.82 m, assuming that the original pile plan was probably designed with a spacing of 1.82 m.

[0051] The rounding means may correct the reference axis of the plurality of elements E·E . . . aligned on the reference axis by the above-described alignment function so that the reference axis has a predetermined coordinate value. In addition, both the alignment function and the rounding function may be implemented, or only one of them may be implemented.

[0052] In this way, by using the system 100 shown in FIG. 1, it is possible to easily calculate the actual dimensional position coordinates of the element E from the image data D in which digital information regarding dimensions and geometric shape has been lost.

[0053] Next, a specific element position calculation method will be described with reference to Fig. 2 to Fig. 7. In the following description, the framing plan will be a pile framing plan, and the element E will be a pile. First, in step S1 of Fig. 2, a user U operates a customer terminal C to read image data D of a pile plan and transmit it to the system 100. Fig. 3 shows the state in which the transmitted image data D is displayed on the customer terminal C.

[0054] This image data D is raster data obtained by scanning a paper drawing with a scanner S, but it may be slightly tilted due to the effects of scanning. In this case, the tilt can be corrected by using the straight line part of the drawing frame.

[0055] Next, in S2: element detection step, elements E·E... are detected from the read image data D by an image classification system using machine learning. Thirty detected stakes are displayed as markers in Figure 4. Looking at the leftmost column, five stakes are lined up vertically, and to the right of them are four stakes, so multiple stakes are detected lined up vertically. Also, looking at the top row, five stakes are lined up horizontally, and below that there are three stakes, and so on, with multiple stakes detected lined up horizontally.

[0056] The foundation of a typical building is made up of elements arranged in a perpendicular grid pattern, so if the horizontal and vertical directions of the foundation are considered to be a Cartesian coordinate system, as shown in Figure 4, it is common for multiple elements E·E... to be detected as being lined up in the direction along that coordinate system.

[0057] Next, in S3: alignment step, slight positional deviations of the elements E·E... read in S2: element detection step are corrected. For example, it can be seen that the center lines of the five elements E1 to E5 lined up vertically on the far left side of Fig. 4 are slightly misaligned in the horizontal direction. Note that the amount of misalignment is exaggerated in Fig. 4.

[0058] Therefore, in the alignment step, if the amount of deviation is, for example, within one-third of the width of the marker, it is determined that there was a detection error and is corrected. Figure 5 shows the result of correction so that the center lines of the five elements E1 to E5 are aligned vertically. In this case, the reference axis for alignment is, for example, the axis passing through the midpoint coordinate between E1 and E5, which are the furthest apart on the left and right of the five elements E1 to E5. Similarly, other elements E·E... arranged vertically and elements E·E... arranged horizontally are also aligned.

[0059] Next, in S4: coordinate calculation step, coordinate values of actual dimensions from the reference position are calculated for each of the aligned elements E·E.... The coordinate calculation step can be composed of, for example, S41: reference dimension determination step and S42: subtraction dimension calculation step. S41: In the reference dimension determination step, the dimension of the gap between the leftmost element E1 and the rightmost element E27 shown in FIG. 5 is read and input. The actual dimension value of the read dimension is recorded as reference dimension information. The dimension may be read visually by a user U, or may be read automatically by image detection. Then, calculate the coefficient so that the dimension read in this way matches the system distance value of the farthest element E1·E27. The same applies to the vertical coordinate.

[0060] S42: In the step of calculating the extrusion dimension, an extrusion dimension is calculated for each detected element E, which is a cumulative dimension instruction from the reference position. Any position can be selected as the reference position, but for example, the coordinates of the element E1 located at the top left can be set as the reference position information. This reference position can be set in advance to be the top left element E1, or the user U can manually select and determine any element E.

[0061] Then, the position coordinates of each element E·E... are calculated in actual dimensions using the coefficients calculated from the above-mentioned reference dimension information and the reference position information, to obtain the offset dimensions. The calculated displacement dimensions are shown in Fig. 6.

[0062] Finally, in S5: rounding step, the reference axes of the plurality of elements E·E... aligned on the reference axes in S3: alignment step are corrected so that they have predetermined coordinate values. For example, in FIG. 6, the second vertically arranged elements from the left (E6 to E9 in FIG. 5) are aligned by the alignment step, and as a result, the dimension from the reference position is 1815.4 mm (1.8154 m).

[0063] However, when designing the position of the piles, it is not possible to design it to an odd size such as 1.8154 m, so it is highly likely that this size was originally designed to be 1820 mm (1.82 m), or 1 ken, and it is thought that the center coordinates were slightly shifted due to a detection error in the S1: element detection step.

[0064] Therefore, assuming that this dimension should be 1820 mm in design, it is corrected to 1820 mm by the rounding step S5, as shown in Figure 7. The same applies to the rows and columns of the other elements E·E... However, for example, in the case of the dimensions of element E18 in Figure 5 (the dimension of 5156.7 mm in Figure 6), which are clearly deviated from the specified standard spacing by more than the margin of error, it is assumed that the placement in such a deviated position is correct, and the element is not subjected to the rounding step.

[0065] Image data D, in which the position coordinates of each element E·E... are calculated from the framing plan using the above method, can be output as PDF data or paper drawings. It is also possible to output the array of each coordinate value as CSV data.

[0066] When output as CSV data, for example, it is possible to have a pile driver read the CSV data at the actual work site and control it so that it automatically drives piles into the locations of the coordinate values, making design and construction work easier.

[0067] In any step, the user U can manually modify the color, thickness, size, etc. of elements and dimension lines, draw shapes, and input text. Furthermore, in S42: the step of calculating the removal dimensions, the calculated coordinate values may be manually corrected.

[0068] Furthermore, in calculating coordinate values, it is possible to calculate not only coordinate values in a Cartesian coordinate system but also diagonal dimensions in diagonal directions. In this case, a method of automatically calculating the diagonal dimension of the post at the diagonal position with the furthest distance, or a method of manually selecting any post and calculating the diagonal dimension of that post can be adopted.

[0069] In addition to the diagonal dimensions, the device can also be configured to calculate dimensions between any two points that have a predetermined angle with respect to the Cartesian coordinate system, or the area of a figure obtained by selecting multiple coordinates.

[0070] "Variation 1" Next, an element position calculation system 101 according to a modified example of the present invention will be described with reference to Fig. 8. In the following description, the same parts will be denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0071] This modified example differs from the forms shown in Figures 1 to 7 in that the floor plan is a roof floor plan, and element E is a mixture of multiple elements such as roof beams and pipe columns. In this modification, the element detection means 1 is adjusted to have an image classification system that can detect a plurality of elements separately.

[0072] Then, the separately detected rafters and pipe columns have their respective displacement dimensions calculated from the reference position. The dimensions can be displayed on the screen of the customer terminal C, for example, in different colors.

[0073] By configuring as described above, even if multiple elements are shown on one framing plan, as in this modified example, the position coordinates of these elements can be calculated as separate elements. [Explanation of symbols]

[0074] 100,101 Element position calculation system 1. Element detection method 2 Alignment Method 3. Coordinate calculation method 31 Means for determining reference dimensions 32 Method of calculating displacement dimensions 4 Rounding Methods C. Customer terminal D. Image data The E element U User S scanner

Claims

1. An element position calculation system for calculating the position coordinates of each element from image data of a floor plan on which a plurality of elements for construction are described, an element detection means for detecting the position of the element from the image data; An element position calculation system comprising a coordinate calculation means for calculating the position coordinates of each element from reference dimension information, which is actual dimensions, and reference position information of the building.

2. the element is a pile; 2. The element position calculation system according to claim 1, wherein the system calculates the position coordinates of each pile from image data of a pile plan showing a plurality of piles.

3. 3. The element position calculation system according to claim 1, wherein the element detection means uses an image classification system based on machine learning.

4. further comprising alignment means; 4. The element position calculation system according to claim 3, wherein the alignment means aligns and arranges positions of the plurality of elements detected by the element detection means, which are arranged in rows within a predetermined error range in each direction of the Cartesian coordinate system, on a reference axis of each row.

5. further comprising a rounding means; 5. The element position calculation system according to claim 4, wherein the rounding means is configured to correct both or either of the plurality of elements detected by the element detection means and the plurality of elements aligned on the reference axis so as to have predetermined coordinate values in any direction of the Cartesian coordinate system.

6. An element position calculation method for calculating position coordinates of each element from image data of a floor plan on which a plurality of elements for construction are described, an element detection step of detecting the position of the element from the image data; An element position calculation method comprising a coordinate calculation step of calculating the position coordinates of each element from reference dimension information, which is actual dimensions, and reference position information of the building.

7. the element is a pile; The element detection step uses an image classification system based on machine learning, 7. The element position calculation method according to claim 6, wherein the position coordinates of each pile are calculated from image data of a pile plan showing a plurality of piles.

8. further comprising an alignment step and a rounding step; The alignment step aligns and arranges the positions of the plurality of elements detected in the element detection step, among the plurality of elements that are arranged in rows within a predetermined error range in each direction of the Cartesian coordinate system, on a reference axis of each row, and 8. The element position calculation method according to claim 7, wherein the rounding step corrects, in any direction of the Cartesian coordinate system, both or either of the plurality of elements detected in the element detection step and the plurality of elements aligned and arranged on the reference axis so as to have predetermined coordinate values.

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