KR20210102155A - Apparatus and Method of Processing for Real Estate Information - Google Patents

Abstract

The present invention relates to a real estate information processing device and method. According to the present invention, the real estate information processing device includes the steps of: selecting a real estate property; displaying a 3D drawing of the selected real estate property; changing a property of an object selected in the 3D drawing; and recommending at least one company in response to the object of which properties have been changed. Therefore, the user can check real estate information more conveniently and quickly.

Description

Apparatus and Method of Processing for Real Estate Information

The present invention relates to a real estate information processing apparatus and method.

Real estate transactions such as apartments are active in Korea these days.

Buyers who have purchased a house such as an apartment can renovate the interior of the house according to their wishes. In this case, it is common for the buyer to call an interior designer to check the structure of the house, and then receive an estimate from the contractor.

However, in this case, there is a problem in that it takes a considerable amount of time to confirm the estimate.

An object of the present invention is to provide a real estate information processing apparatus and method that can quickly check real estate information.

The real estate information processing method according to the present invention includes a selection step of selecting a real estate object, a display step of displaying a 3D drawing of the selected real estate object, a changing step of changing a property of an object selected in the 3D drawing, and the property It may include a recommendation step of recommending at least one company in response to the changed object.

In addition, extracting an image file of the selected real estate object, extracting coordinate data based on the extracted image file, and constructing a 3D drawing of the real estate object based on the coordinate data. can

Also, the image file may include a sketch file.

In addition, the object may include at least one of a wall, a floor, a window, a door, a ceiling, a bathtub, a toilet, a washbasin, furniture, home appliances, machines, equipment, curtains, and blinds.

In addition, the attribute may include at least one of design, color, pattern, shape, material, size, and performance.

In addition, in the recommendation step, at least one company may be recommended according to the order of the lowest price in the estimate in response to the object whose properties have been changed.

In addition, in the recommendation step, at least one company may be recommended in the order of the highest ratings corresponding to the objects whose properties have been changed.

In addition, it may further include the step of providing a quote of the recommended company.

A real estate information processing apparatus according to the present invention includes a real estate server for storing information on at least one real estate object and a user terminal accessing the real estate server, wherein the real estate server includes the user terminal using at least a first real estate object. When selected, a 3D drawing of the selected first real estate object is provided to the user terminal, and the real estate server, when changing a property of an object selected in the 3D drawing provided by the user terminal, the property Recommendation information for recommending at least one company in response to the changed object may be provided to the user terminal.

In addition, including a company server of the company, the real estate server transmits a 3D drawing in which the properties of the object are changed to the company server, and the company server provides an estimate corresponding to the 3D drawing received from the real estate server. It can be transmitted to at least one of the server or the user terminal.

In addition, including a company server of the company, the real estate server transmits information about the object whose properties are changed to the company server, and the company server provides a quote corresponding to the object received from the real estate server. It can be transmitted to at least one of the server or the user terminal.

In addition, the real estate server may provide the quotation received from the company server of the recommended company to the user terminal.

In addition, the real estate server may receive the quotation from a plurality of the company servers, and recommend and provide the quotation of at least one company to the user terminal in the order of the lowest price quoted.

In addition, the real estate server may receive the quotation from a plurality of the business server, and recommend and provide the quotation of at least one business to the user terminal in the order of the highest rating.

In addition, the real estate server extracts an image file of the selected first real estate object, extracts coordinate data based on the extracted image file, and constructs a 3D drawing of the first real estate object based on the coordinate data can do.

Also, the image file may include a sketch file.

In addition, the object may include at least one of a wall, a floor, a window, a door, a ceiling, a bathtub, a toilet, a washbasin, furniture, home appliances, machines, equipment, curtains, and blinds.

In addition, the attribute may include at least one of color, pattern, shape, material, size, and performance.

The real estate information processing apparatus and method according to the present invention have the effect of allowing a user to more conveniently and quickly check real estate information by converting an image of a real estate object into a 3D drawing and providing it.

1 to 2 are diagrams for explaining the configuration of a file conversion apparatus according to an embodiment of the present invention.
3 to 7 are diagrams for explaining a first embodiment of a method of drawing an image file.
8 to 11 are diagrams for explaining a second embodiment of a method of drawing an image file.
12 to 14 are diagrams for explaining the configuration and schematic functions of the real estate information processing apparatus according to the present invention.
15 to 27 are diagrams for explaining a real estate information processing method.

Hereinafter, a real estate information processing apparatus and method according to the present invention will be described in detail with reference to the accompanying drawings.

Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail in the detailed description. This is not intended to limit the present invention to a specific embodiment, it can be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention.

In describing the present invention, terms such as first, second, etc. may be used to describe various components, but the components may not be limited by the terms. The above terms may be used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component.

The term and/or may include a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being “connected” or “connected” to another component, it may be directly connected or connected to the other component, but other components may exist in between. can be understood On the other hand, when it is mentioned that a certain element is "directly connected" or "directly connected" to another element, it may be understood that the other element does not exist in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression may include the plural expression unless the context clearly dictates otherwise.

In the present application, terms such as "comprise" or "have" are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, and one or more other features It may be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded in advance.

Unless defined otherwise, all terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary may be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in the present application, it is interpreted in an ideal or excessively formal meaning. it may not be

The following embodiments are provided to more completely explain to those of ordinary skill in the art, and the shapes and sizes of elements in the drawings may be exaggerated for clearer description.

Various embodiments described below may be implemented in a computer-readable recording medium using software, hardware, or a combination thereof.

According to the hardware implementation, the embodiment of the present invention is ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays, processors) It may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and electrical units for performing functions.

On the other hand, according to the software implementation, embodiments such as procedures or functions in the present invention may be implemented together with a separate software module for performing at least one function or operation.

1 to 2 are diagrams for explaining the configuration of a file conversion apparatus according to an embodiment of the present invention.

Referring to FIG. 1 , the file conversion apparatus includes an input unit 10 , an image file processing unit 20 , and a storage unit 30 .

The input unit 10 is a part for receiving a file for drawing, and may be implemented as a communication module for inputting or downloading a file through a USB port or a network for receiving a file input through an external device.

Here, the file for drawing may include at least one of an image file (JPG file, GIF file, PNG file, etc.) and PDF file. The PDF file may mean a file imaged through its own algorithm.

Alternatively, the image for drawing may refer to an image obtained by photographing a drawing drawn by a user. Alternatively, it may be an image file (JPG file, GIF file, PNG file, etc.) and PDF file generated by taking a drawing drawn by the user. Here, the PDF file may mean a file imaged through its own algorithm.

On the other hand, the image file processing unit 20 serves to store in the storage unit 30 by drawing (2D drawing and/or 3D drawing) a file input through the input unit 10 .

As shown in FIG. 2 , the image file processing unit 20 includes an outline extraction module 21 , a corner feature point detection module 22 , a point connection module 23 , a noise removal module 24 , and an image detection module 25 . , template matching module 26, 2D drawing generation module 27, 3D drawing calculation module 28, lighting effect removal module 31, labeling module 33, boundary line detection module 34, direction determination and outline removal A module 35 may be included.

The outline extraction module 21 may extract an outline from the input file. In addition, the outline extraction module 21 may extract an outline from the image from which the influence of lighting is removed, and store the resultant image.

The corner feature point detection module 22 may detect and coordinate the corner feature points based on the extracted outline.

The point connection module 230 may connect the detected corner feature points with a line.

The noise removing module 24 may remove noise from the connected lines.

The image detection module 25 may detect an image from which an outline has been removed.

The template matching module 26 may perform template matching between the image from which the noise has been removed and the image from which the outline has been removed. Alternatively, the template matching module 26 may perform template matching between the image from which the outline is removed and the image from which the influence of lighting is removed.

The 2D drawing generation module 27 may generate a 2D drawing for the input file by applying the stored outer coordinate information and element coordinate information to the CAD program.

The 3D drawing calculation module 28 may calculate a 3D drawing based on the generated 2D drawing.

The rough surface effect removal module 31 converts drawing information (image) into a Lab channel, separates the converted Lab channel into each channel, and processes the contrast of the separated L channel to remove the influence on lighting .

The labeling module 33 may detect the blob by labeling the image from which the outline is extracted.

The boundary line detection module 34 may detect a boundary line based on the detected blob.

The directionality determination and outline removal module 35 samples a set of innumerable points constituting the detected boundary line to determine the directionality, detects the outline, removes the effect of lighting, and smoothes the image using a median filter to extract the outline. It is possible to detect an image from which the outline has been removed by calculation.

A file conversion method using the above file conversion apparatus will be described below with reference to the accompanying drawings.

3 to 7 are diagrams for explaining a first embodiment of a method of drawing an image file. Hereinafter, the description of the above-described parts may be omitted.

3 is a flowchart illustrating a file conversion method according to the first embodiment of the present invention, and converts image files such as JPG files, GIF files, PNG files, or document files such as PDF files to usable files such as CAD files. It shows how to draw.

Referring to FIG. 3 , the file conversion method according to the first embodiment of the present invention includes (a) receiving a drawing target file (S101); (b) extracting the outline from the input file (S102 ~ S104); (c) detecting and coordinated corner feature points based on the extracted outline (S105); (d) connecting the detected corner feature points with a line (S106); (e) removing noise from the lines connected in step (d) (S107); (f) detecting an image from which the outline has been removed from the input file (S108); (g) template matching the image from which the noise has been removed in step (e) and the image detected in step (f) (S109); (h) generating a 2D drawing for the input file by applying the pre-stored outer coordinate information and element coordinate information to a CAD program after matching the template in step (g) (S110); (i) calculating a 3D drawing based on the 2D drawing generated in step (h) (S111).

Meanwhile, the step (b) includes (b1) converting the input image file information to a gray scale (S102); (b2) performing truncation coding by bit-plane slicing the grayscale-converted information, storing the most significant bit information image among the truncation-encoded information, and converting the truncation-encoded information to a median It may include steps (S103 to S104) of extracting an outline by smoothing using a filter (Median Filter) and storing the resultant image.

In step (f), information on valid linear components in the noise-removed image is stored, the element is detected when the outline detection is completed, and the image obtained by smoothing the converted grayscale image and the median filter to extract the outline. It is possible to detect an image from which the outline has been removed by calculation.

In addition, the step (h) stores the position value of the element matched in the template matching, calculates the position value of the image on which the outer detection is completed and the stored element to extract element coordinate information, and the outer coordinate information and the element coordinate information can be applied to CAD programs to make 2D drawings of input files (image files, PDF files).

Hereinafter, the file conversion method according to the first embodiment of the present invention will be described in more detail.

First, a drawing target file to be drawn is received through the input unit 10 (S101). Here, the file to be drawn includes at least one of an image file (JPG file, GIF file, PNG file, etc.) and PDF file. 4 is an exemplary diagram in the case where the received file is an image file.

When an image file is input, the image file processing unit 20 processes and draws the input image file. For example, the input image file information is converted into gray scale (image 1) (S102). A digital image refers to an image in which the value of each pixel is one sample, and only information of luminance can be transmitted. This kind of image, also known as black and white, consists of gray shadows, ranging from the softest "black" to the strongest "white". Therefore, by converting the image file information into grayscale, the brightness of each pixel can be determined.

Next, truncation coding is performed on the grayscale-converted image information using a bit-plane slicing method. That is, lossy compression.

For example, one pixel of an 8-bit gray image consists of 8 bits, and among the 8 bits, the most significant bit is called MSB and the least significant bit is called LSB. Lossy compression is performed by truncating the lower 4 bits.

Thereafter, the most significant bit information image (image 2) among the truncation-encoded information is stored in the storage unit 30, the truncation-encoded image information is smoothed using a median filter to extract an outline, and the result Save the image (image 3).

Here, smoothing using the median filter means replacing the average value of the intensity of each pixel with the median value of the intensity within points surrounding the pixel. This smoothing method is particularly effective when the noise form is strong and consists of elements such as elongated lines, and edge sharpening is well preserved.

4 shows an example of an image file to be converted into a drawing file by the file conversion method according to the first embodiment, and FIG. 5 shows an example of a result of extracting an outline from the image file shown in FIG. .

Next, corner feature points are detected and coordinated based on the extracted outline in step S105.

6 shows an example of a result of extracting corner feature points from the image file.

For example, the corner image (image 4) is detected through Harris corner detection on the image information from which the outline is extracted, and the corner feature point is calculated by calculating the outline detection image (image 3) and the corner image (image 4). can be detected.

Here, when Harris Corner Detection creates and searches an arbitrary area (Window) in the image, a point where there is no change in all directions or changes in all directions rather than only in a certain direction along the edge is the corner. It is an algorithm that recognizes points (edges).

Next, the corner feature points detected in step S106 are connected with a line (image 5). Thereafter, noise is removed from the connected lines in step S107.

For example, noise on the continuous lines may be removed by calculating (logical product) an image (image 5) in which the outline is connected to the detection image (image 3) and corner feature points are connected with a line.

Next, in step S108, an image from which the outline is removed from the image file is detected.

For example, information on a valid linear component in an image from which noise is removed may be stored, and an element may be detected in an image (image 6) in which outlier detection is completed.

Here, the element may mean an image other than an outline in the image file as shown in FIG. 4 . For example, a door, a window, a sink, etc. may be said to be the said element.

Then, the image from which the outline has been removed may be detected by calculating the converted grayscale image (image 1) and the image (image 3) obtained by smoothing and extracting the outline using the median filter.

Thereafter, in step S109, the image from which the noise has been removed and the image from which the element is detected are subjected to template matching.

7 illustrates an example of a state in which a noise-removed image and an image in which elements are detected are matched with a template.

For example, an image in which noise is removed and an image in which elements are detected may be superimposed.

Here, the template matching may be performed by prioritizing a door, a window, a washbasin, and the like.

Next, after matching the template in step S110, the pre-stored outer coordinate information and element coordinate information may be applied to the CAD program to generate a 2D drawing for the input file.

For example, the element coordinate information is extracted by storing the position value of the element matched in the template matching (image 7), calculating the image where the outline detection is completed (image 6) and the stored element position value (image 7) In addition, by applying the outer coordinate information and element coordinate information to the CAD program, the image file can be 2D drawn.

Thereafter, in step S111, a 3D drawing is calculated based on the generated 2D drawing. Here, a method of calculating a 2D drawing into a 3D drawing may be performed using Rhino, 3D MAX, AutoCad, Archicad program, or the like.

According to one embodiment of the present invention as described above, image files such as JPG files, GIF files, PNG files, etc. or document files such as PDF files can be drawn, so that the image files can be reused, and the image files Convenience of use can be promoted by drawing by automatic program without user's manual work.

On the other hand, in addition to the general 2D image file, an image of a user's hand-drawn drawing, for example, an image file (JPG file, GIF file, PNG file, etc.) It may also be possible to process and convert it into a 3D drawing. Hereinafter, referring to the accompanying drawings, it will be described.

8 to 11 are diagrams for explaining a second embodiment of a method of drawing an image file. Hereinafter, the description of the above-described parts may be omitted.

8 is a flowchart illustrating a drawing method of an image according to a second embodiment of the present invention. (a) converting drawn drawing information into a Lab channel (S201 to S202); (b) separating the Lab channel converted in step (a) into respective channels, and processing the contrast of the separated L channel to remove the influence on lighting (S203); (c) extracting an outline from the image from which the effect of lighting is removed in step (b) and storing the resultant image (S204); (d) detecting the blob by labeling the image stored in the step (c) (S205); (e) detecting and storing a boundary line based on the detected blob (S206); (f) determining a direction by sampling a set of innumerable points forming the detected boundary line and detecting an outline (S207); (g) detecting the image from which the outline has been removed by calculating the image from which the influence of lighting has been removed in step (b) and the image obtained by smoothing the image using a median filter to extract the outline (S208); (h) template matching between the image from which the outline is removed in step (g) and the image in which the element is detected (S209); (i) generating a 2D drawing for the input image by applying the pre-stored outer coordinate information and element coordinate information to a CAD program after matching the template in step (h) (S210); (j) may include a step (S211) of calculating a 3D drawing based on the 2D drawing generated in step (i).

The drawing conversion method according to the second embodiment will be described with reference to FIGS. 1 and 2 above.

First, an image to be drawn is received through the input unit 10 (S201). The image to be drawn here is a drawing drawn by the user (a sketched drawing). For example, a user draws a drawing by hand to produce a design drawing. Then, image information is generated by photographing the drawn drawing using a photographing means such as a camera. That is, image information such as a JPG file, a GIF file, and a PNG file is generated by taking a drawn drawing.

When the image information is input, the image file processing unit 20 processes the input image information to make a drawing. For example, drawing information (image information) drawn in the lighting effect removal module 31 is converted into a Lab channel (image 1) (S202). That is, the drawn drawing information is converted into an L channel having light and dark information, and a channel and b channel having color information.

Next, the effect of lighting is removed for the converted Lab channel. That is, only the image information of the actually drawn drawing is extracted by removing the effect of lighting generated when photographing the drawn image information.

To this end, as shown in FIG. 9, the converted Lab channel is separated into each channel (L channel, a channel, b channel) (S301), and the separated L channel is filtered with a median filter to remove noise ( S302). Here, the higher the order of the median filter, the better, but in the present invention, it is set to 51. This is because the higher the order, the lower the performance, so the optimal order value to obtain performance was set to 51. If the L-channel image is filtered with a median filter, the surrounding noise information is blurred, leaving only the flow of light. Therefore, in order to remove the lighting effect of the image, the light flow is extracted from the image by filtering the L channel with a median filter. Thereafter, the L channel from which the noise has been removed is inversely transformed (Not) (L_channel_not) (S303), and the inversely transformed image (L-channel_not) and the L channel image are merged (Merge) to remove the effect of illumination (S304).

Next, in step S304, the most significant bit information is received through bit slicing from the image from which the influence of lighting is removed, the image (image 2) in which only the outline information is expressed is extracted and stored in the storage unit 30 .

Thereafter, a blob is detected by labeling the stored image (S205).

Here, since labeling is an image processing technique that is basically applied in image processing, a detailed description thereof will be omitted. Next, a boundary line (vector) is detected and stored based on the detected blob (image 3) (S206). Here, the boundary line is the process of detecting the largest image from the detected blob.

Thereafter, by sampling a set of innumerable points forming the detected boundary line, the direction is determined and the outline is detected (image 4) (S207).

For example, as shown in FIGS. 10 and 11, cross-product calculation is performed on a Y-axis normal vector and a vector for two points on the x and z axes in a 3D environment based on the detected boundary line image (B = TxN) (S301). Then, the cross product operation result for each point is normalized to a vector having a magnitude value of 1, and magnitude values of each vector are compared (S302). In addition, the correlation of each point is analyzed based on the result of comparing the magnitude values of each vector (S303), and the direction of each set of points is determined based on the analyzed correlation (S304) to extract the outline. .

Here, the outline extraction refers to an operation of sampling points by finding a correlation with each other while finding N in the drawing as shown in FIG. 11 . Correlation refers to a relationship whether in the same direction or in a different direction. If the set of several points is defined as a straight line, the direction of N has almost the same direction.

Thereafter, the sampled points are stored as outlines.

When the outline detection is completed through this process, the process moves to step S208 to detect and store the image from which the outline has been removed (image 5). For example, information on a valid linear component in an image from which noise is removed is stored as an outline, and when the outline detection is completed, the element is detected. The element detection is to detect an image from which the outline has been removed by calculating an image from which the influence of the illumination has been removed and an image obtained by smoothing the image using a median filter and extracting the outline.

Next, the image in which the outline is removed and the image in which the detected element is detected are matched with a template (S109). For example, the image from which the outline is removed and the image in which the element is detected are superimposed. Here, in the template matching, it is preferable to template matching the door/window/wash basin with priority.

Thereafter, after template matching in step S210, the pre-stored outer coordinate information and element coordinate information are applied to the CAD program to generate a 2D drawing for the input file. For example, the position value of the element matched in the template matching is stored, the element coordinate information is extracted by calculating the position value of the image on which the outline detection is completed and the stored element, and the outline coordinate information and the element coordinate information are applied to the CAD program. 2D drawing of the image file.

Thereafter, in step S211, a 3D drawing is calculated based on the generated 2D drawing. Here, as a method of calculating a 2D drawing into a 3D drawing, a general Rhino, 3D MAX, AutoCad, or Archicad program may be used.

According to the present invention described above, it is possible to easily draw a hand-drawn drawing as a design drawing, and there is an advantage in that the user can conveniently and freely calculate various design drawings. In particular, by drawing image information by an automatic program without the user's manual work, it is very convenient.

It is possible to use the 3D drawing converted according to the method described above as real estate information. Hereinafter, referring to the accompanying drawings, it will be described.

12 to 14 are diagrams for explaining the configuration and schematic functions of the real estate information processing apparatus according to the present invention. Hereinafter, the description of the above-described parts may be omitted.

12 , the real estate information processing apparatus 1 according to the present invention may include a user terminal 100 and a real estate server 200 . In addition, the real estate information processing apparatus 1 may further include a company server 300 .

The real estate server 200 may store information on at least one real estate object. The real estate object may include information for identifying a location, such as an address, GPS coordinates, a building name, and the number of a building.

A user may access the real estate server 200 using the user terminal 100 . The user terminal 100 may be a mobile communication terminal such as a smart phone, or a fixed terminal such as a desktop.

The real estate server 200 may provide, to the user terminal 100 , a 3D drawing of the selected first real estate object, for example, when the user terminal 100 selects at least a first real estate object. In addition, the real estate server 200, when the user terminal 100 changes the properties of the object selected in the 3D drawing, the user terminal ( 100) can be provided.

The company server 300 may provide an estimate. Here, the company server 300 may be a server of various companies. For example, the company server 300 may be various, such as a server of an interior company, a server of a furniture company, a server of a machine manufacturing company, and the like. Hereinafter, for the convenience of explanation and understanding, the server of the interior company will be described as an example for the company server 300 .

Referring to FIG. 13 , the real estate server 200 may include an image file processing unit 20 and a storage unit 210 .

The storage unit 210 may store information on real estate objects. For example, the storage unit 210 may store an image file for a real estate product. Here, the image file for the real estate object may include a sketch file. The sketch file may be a file for an image drawn directly by the user.

The function of the image file processing unit 20 will be schematically described with reference to the attached FIG. 14 as follows.

As shown in FIG. 14 , the image file processing unit 20 may extract an image file for a real estate object stored in the storage unit 210 ( S500 ).

Thereafter, coordinate data may be extracted based on the extracted image file (S510), and a 3D drawing of a real estate product may be configured based on the coordinate data (S520).

Here, since the method of extracting coordinate data based on the image file has been described in detail with reference to FIGS. 1 to 11 above, further description thereof will be omitted.

A real estate information processing method using the real estate information processing device 10 described above will be described as follows.

* FIGS. 15 to 27 are diagrams for explaining a real estate information processing method. Hereinafter, the description of the above-described parts may be omitted.

Referring to FIG. 15 , when the user terminal 100 accesses the real estate server 200 first, real estate information may be displayed on the screen of the user terminal 100 ( S600 ). For example, as in the case of FIG. 16 , real estate information based on a map may be displayed on the screen of the user terminal 100 . Here, the real estate information may include information on at least one real estate product.

Thereafter, it may be determined whether the user terminal 100 selects a real estate product (S610).

As a result of the determination, when a real estate object is selected, a 3D drawing of the selected real estate object may be displayed on the screen of the user terminal 100 ( S620 ). An example of a 3D drawing of a real estate object is disclosed in FIG. 17 .

In this way, when the real estate object is displayed in a 3D drawing, it is possible for the user to more easily and accurately check the desired real estate object information.

In this document, a residential apartment is described as an example of a real estate product, but the present invention may not be limited thereto. For example, real estate objects may be various, such as shopping malls and factories.

Thereafter, it may be determined whether to change the properties of the object selected in the 3D drawing displayed on the screen ( S630 ).

Hereinafter, an object will be described using a wall as an example, but the present invention may not be limited thereto. In this document, an object may include at least one of a wall, a floor, a window, a door, a ceiling, a bathtub, a toilet, a washbasin, furniture, home appliances, curtains, machines, equipment, and blinds.

The property of the selected object may be changed according to the determination result (S640).

For example, as in the case of FIG. 18 , the user may select the living room wall 300 in the 3D drawing of the real estate object using the user terminal 100 and change the color of the selected living room wall 300 . .

As such, by changing the property (eg, color) of a desired object (eg, a wall) on the 3D drawing of the real estate object, the user can predict and confirm the result of the change without actually changing the attribute of the object.

Hereinafter, the attribute will be described using color as an example, but the present invention may not be limited thereto. In this document, the attribute may include at least one of design, color, pattern, shape, material, size, or performance.

Thereafter, the real estate server 200 may determine whether the user requests the real estate server 200 to provide recommendation information for the real estate object using the user terminal 100 ( S650 ).

Thereafter, according to the determination result, the real estate server 200 may provide recommendation information to the user terminal 100 ( S660 ).

For example, as shown in FIG. 18 , the user may request recommendation information by being satisfied with the color change of the living room wall 300 . Then, the real estate server 200 may provide recommendation information for recommending a company to the user terminal 100 in the form shown in FIG. 19 in response to the color change of the living room wall 300 . 19 may be recommended information including a meaning that it is appropriate to request the interior company A for the construction of changing the color of the living room wall 300 .

In addition, the real estate server 200 may provide a quote of the recommended company to the user terminal 100 . An example of the quotation is disclosed in FIG. 20 . As shown in FIG. 20 , the quotation may include information on a company and information on a price (cost).

Thereafter, it is possible for the user to evaluate the satisfaction of the company recommended by the user terminal 100 ( S670 ).

Meanwhile, the real estate server 200 may request an estimate from a company. This is explained below.

Referring to FIG. 21 , the real estate server 200 transmits the 3D drawing in which the properties (eg, color) of the object (eg, the living room wall 300) are changed to the company server 300 as shown in FIG. 18, and based on this, a quotation is issued. You can make a request (S667). That is, the real estate server 200 sends the 3D drawing itself including the object whose properties are changed by the user to the company, and requests a quote corresponding to the 3D drawing sent.

Thereafter, the real estate server 200 may receive an estimate from the company server 300 ( S662 ).

Thereafter, the real estate server 200 may recommend/provide the quotation received from the company server 300 to the user terminal 100 as recommendation information (S663).

Alternatively, the company server 300 may transmit an estimate corresponding to the information received from the real estate server 200 to at least one of the real estate server 200 or the user terminal 100 . That is, in the company server 300 , it is possible to directly transmit the quotation to the user terminal 100 without going through the real estate server 200 .

Alternatively, as in the case of FIG. 22 , the real estate server 200 does not transmit the 3D drawing to the company server 300 , but only the information about the changed content, for example, an object whose properties are changed, to the company server 300 , and based on this It is possible to request a quotation (S664).

In this case, the company may prepare a quotation only with information on the object whose properties have been changed and transmit it to the real estate server 200 .

Even in this case, the company server 300 may transmit a quote corresponding to the information received from the real estate server 200 to at least one of the real estate server 200 or the user terminal 100 .

On the other hand, the real estate server 200 transmits information to a plurality of company servers 300 , and it is also possible to receive an estimate from the plurality of company servers 300 .

In this case, the real estate server 200 is possible to transmit all quotations to the user terminal 100 . Alternatively, the real estate server 200 may classify a plurality of received quotations and provide only a predetermined number of quotations to the user terminal 100 .

For example, as in the case of FIG. 23 , the real estate server 200 may analyze the received quotation after receiving the quotation from the company server 300 ( S662 ) ( S665 ).

Thereafter, it is possible to check the cost in each estimate (S666).

In addition, it is possible to classify the estimate according to the cost (S667).

For example, as in the case of FIG. 24 , the cost of each interior company may be analyzed by analyzing each estimate received from the interior companies A, B, C, and D. In addition, each estimate can be classified into recommended and non-recommended. In detail, the real estate server 200 may recommend at least one company according to the order of the lowest price (cost) in the quotation received in response to the object whose properties have been changed.

On the other hand, in the real estate server 200, it is possible to provide recommendation information in consideration of the evaluation score (grade) given to each company. Hereinafter, referring to the accompanying drawings, it will be described.

Referring to FIG. 25 , in the recommendation step, a company may be first selected according to a rating ( S668 ). For example, when the user wants to change the color of the living room wall 300 as in the case of FIG. 18 above, the real estate server 200 determines the living room wall 300 color change construction in order of highest rating. You can select any number of companies.

Thereafter, the real estate server 200 transmits a 3D file including an object whose property is changed to the company server 300 of the selected company or transmits information about the object when the property is changed, and requests a quote (S661, S664) )can do.

Thereafter, the real estate server 200 may receive the quotation from the company server 300 ( S662 ), and provide the received quotation as recommendation information to the user terminal 100 ( S663 ).

For example, as in the case of FIG. 26 , the recommendation information provided to the user terminal 100 may include rating information assigned to each of the interior companies A, B, C, and D. In addition, it is possible to set a company whose rating is higher than a preset reference rating as a recommended company.

As such, in the recommendation step, it is possible to recommend at least one company according to the order of the highest ratings corresponding to the objects whose properties are changed.

Alternatively, in the real estate server 200, it is possible to select a recommended company in consideration of the price (cost) on the quotation and the rating of the company.

For example, as in the case of FIG. 27 , it is assumed that the immovable server 200 receives quotations from the interior companies A, B, C, and D for the color change of the living room wall 300 , respectively.

The price (cost) on the estimate for interior company A is 1 million won and the rating is 95 points, the price on the quotation for interior company B is 1.2 million won and the rating is 98 points, the price on the quotation for interior company C is 2.5 million won and the rating is 92 points. , D The price on the quotation of the interior company may be 1 million won, and the rating may be 65 points.

Here, assuming that the reference cost is 1.5 million won or less, and the reference score is 90 points or more, the real estate server 200 selects A, B interior companies from among A, B, C, and D interior companies as recommended companies, A, It is possible to provide the quotation received from the company server 300 of the interior company B as recommended information to the user terminal 100 .

As such, those skilled in the art to which the present invention pertains will understand that the above-described technical configuration of the present invention may be implemented in other specific forms without changing the technical spirit or essential characteristics of the present invention.

Therefore, the embodiments described above are to be understood as illustrative and not restrictive in all respects, and the scope of the present invention is indicated by the following claims rather than the foregoing detailed description, and the meaning and scope of the claims And all changes or modifications derived from the equivalent concept should be construed as being included in the scope of the present invention.

Claims (13)

An information processing method of a real estate information processing device, comprising:
a selection step of selecting a real estate object;
constructing a 3D drawing of the real estate object based on the selected image file of the real estate object;
a changing step of changing the selected object in the 3D drawing; and
Comprising a recommendation step of recommending at least one company in response to the changed contents of the object,
The image file includes a drawing image file,
Constructing the 3D drawing comprises:
processing the contrast of the drawing image file;
extracting an outline from the contrast-processed image;
detecting an element according to template matching with respect to the image from which the outline has been removed from the contrast-processed image;
generating a 2D figure corresponding to the drawing image by applying the outline and element information detected according to the template matching to a CAD program; and
Real estate information processing method comprising the step of calculating the 3D drawing based on the generated 2D figure. The method of claim 1,
The step of processing the contrast,
Separating the drawing image file into each color channel, and removing the influence on lighting by processing the contrast of the brightness channel among the separated channels;
How real estate information is processed. The method of claim 1,
The step of extracting the outline is
extracting an outline from the contrast-processed image and storing the resultant image;
detecting a blob by labeling the stored result image;
detecting and storing a boundary line based on the detected blob; and
Determining a direction by sampling a set of points forming the detected boundary line and detecting an outline; including
How real estate information is processed. The method of claim 1,
The object includes at least one of a wall, a floor, a window, a door, a ceiling, a bathtub, a toilet, a washbasin, furniture, a home appliance, a machine, equipment, a curtain, or a blind. The method of claim 1,
In the recommendation step, a method of recommending at least one company according to the order of the lowest price in the estimate among the companies corresponding to the changed contents. The method of claim 1,
In the recommendation step, a method of recommending at least one company in the order of the highest rating corresponding to the changed content. The method of claim 1,
Method further comprising the step of providing a quote of the recommended company. A real estate server that stores information about at least one real estate object,
The real estate server, when the user terminal selects at least a first real estate object, constructs a 3D drawing of the real estate object based on the image file of the selected first real estate object, and configures the selected first real estate object provides the 3D drawing for the user terminal,
The real estate server, when the user terminal changes the object selected in the 3D drawing, provides recommendation information for recommending at least one company to the user terminal in response to the changed contents of the object,
The image file includes a drawing image file,
The real estate server, in composing the 3D drawing, processes the contrast of the drawing image file, extracts an outline from the image on which the contrast is processed, and the outline is removed from the image on which the contrast is processed. An element is detected according to template matching, the outline and element information detected according to the template matching are applied to a CAD program to generate a 2D figure corresponding to the drawing image, and based on the generated 2D figure, the Characterized in calculating a 3D drawing
Real Estate Information Processing Unit. 9. The method of claim 8,
Further comprising a company server of the company,
The real estate server transmits the 3D drawing in which the object is changed to the company server,
The company server is a real estate information processing device for transmitting the estimate corresponding to the 3D drawing received from the real estate server to at least one of the real estate server or the user terminal. 10. The method of claim 9,
Further comprising a company server of the company,
The real estate server transmits the changed content information of the object to the company server,
The company server is a real estate information processing device for transmitting a quotation corresponding to the object received from the real estate server to at least one of the real estate server or the user terminal. 11. The method of claim 10,
The real estate server is a real estate information processing device for providing the quotation received from the company server of the recommended company to the user terminal. 12. The method of claim 11,
The real estate server receives the quotation from a plurality of the company servers,
A real estate information processing apparatus for recommending and providing an estimate of at least one company to the user terminal in the order of lowering the estimated price corresponding to the changed content information of the object. 12. The method of claim 11,
The real estate server receives the quotation from a plurality of the company servers,
A real estate information processing device for recommending and providing an estimate of at least one company to the user terminal in the order of the highest rating corresponding to the changed content information of the object.

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