JP2014164629A - Information processor, and degree of putting in order determination method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To automatically determine a degree of putting in order.SOLUTION: According to an information processor, a CPU extracts an image of a determination object of a degree of putting in order from a picked-up image of a determination object area imaged by a camera (S103), measures a previously determined item of an extraction object (an image of the determination object) extracted from the picked-up image with extraction processing (S104), determines a degree of putting the determination object in order on the basis of the measurement result and a reference value (S110), and displays the determination result in a display part.

Description

  The present invention relates to an information processing apparatus, a method for determining a degree of order, and a program.

  Conventionally, a dangerous area where furniture falls is taken from indoor images captured by a camera, and when an earthquake early warning is obtained, it is determined whether the resident is in a safe area or a dangerous area, and warning information corresponding to the degree of danger is issued. A technique is known (see, for example, Patent Document 1).

JP 2010-197101 A

  By the way, in offices and workplaces, in order to improve work efficiency and prevent accidents, there is a danger that the desks, floors, cabinets, etc. are organized and things are piled up and protruding. Safety and health patrols may be conducted to check for signs. However, the degree of organization and the degree of danger were judged by human eyes, and the criteria were ambiguous. In addition, many people have to make decisions by participating in safety and health patrols, which has a problem of poor work efficiency.

  In the technique described in Patent Document 1, it is possible to know an area where furniture may fall over in the event of an earthquake. However, the judgment object (for example, desk, floor surface, cabinet, etc.) The degree of organization is not determined.

  An object of the present invention is to enable automatic determination of the degree of organization.

In order to solve the above problem, an information processing apparatus according to claim 1 is provided.
Imaging means;
Extraction means for extracting an image of a determination target of the degree of order and order from a captured image captured by the imaging means;
Measuring means for measuring the value of a predetermined item from the image of the determination object extracted by the extracting means;
Based on the measurement result by the measurement means, a determination means for determining the degree of organization of the determination object,
An output means for outputting a determination result by the determination means;
Is provided.

  According to the present invention, it is possible to automatically determine the degree of order and order of an object to be determined, so it is not necessary to determine the degree of order and order by a person, and the work for determining the degree of order and order can be made more efficient. it can.

It is a block diagram which shows the functional structure of the information processing apparatus in this embodiment. It is a figure which shows the structural example of safety hygiene degree determination software. It is a figure which shows the example of data storage of a reference value data table. It is a figure which shows the example of data storage of a rank determination table. It is a figure which shows the example of data storage of the determination result database. It is a flowchart which shows the safety and health degree determination process performed by CPU of FIG. It is a flowchart which shows the determination process performed in step S10 of FIG. It is a flowchart which shows the extraction process performed in step S103 of FIG. It is a flowchart which shows the measurement process performed in step S104 of FIG. It is a figure which shows an example of the determination result screen.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The present invention is not limited to the illustrated example.

<Configuration of information processing apparatus 1>
First, the configuration of the information processing apparatus 1 according to the present embodiment will be described.
The information processing apparatus 1 is an apparatus that determines the safety and hygiene level of an office, a workplace, a house, and the like. The degree of safety and hygiene is a general term for the degree of organization and risk. As the information processing apparatus 1, for example, a mobile terminal such as a notebook PC (Personal Computer), a tablet, or a handy terminal is applicable.

  FIG. 1 shows a functional configuration example of the information processing apparatus 1. As shown in FIG. 1, the information processing apparatus 1 includes a CPU (Central Processing Unit) 10, a RAM (Random Access Memory) 11, a storage unit 12, a communication unit 13, a display unit 14, an operation unit 15, a camera 16, and the like. Each part is connected by a bus 17.

  CPU10 reads the program memorize | stored in the memory | storage part 12, expand | deploys it to the work area of RAM11, and performs various processes including the safety-hygiene degree determination process mentioned later according to the expand | deployed program. The CPU 10 functions as an extraction unit, a measurement unit, and a determination unit by executing a safety and health level determination process.

  The RAM 11 is a volatile memory, and has a work area for storing various programs executed by the CPU 10, data related to these various programs, and the like.

  The storage unit 12 includes an HDD (Hard Disk Drive), a semiconductor nonvolatile memory, and the like. The storage unit 12 stores a system program executed by the CPU 10, various processing programs, data necessary for executing these programs, and the like. The program is stored in the storage unit 12 in the form of computer-readable program code. The CPU 10 sequentially executes operations according to the program code.

  For example, the storage unit 12 stores safety and health level determination software 121. The safety and health level determination software 121 is a program for causing the CPU 10 to execute a safety and health level determination process to be described later. As shown in FIG. 2, a reference value registration module 121a, a rank registration module 121b, a camera control module 121c, The image comparison module 121d, the measurement result totaling module 121e, and the determination result output module 121f are included.

  Further, the storage unit 12 stores a reference value data table 122, a rank determination table 123, a reference image database 124, a captured image database 125, and a determination result database 126.

  FIG. 3A shows an example of the reference value data table 122. As shown in FIG. 3A, the reference value data table 122 includes a “type” indicating a type (organization degree or degree of risk), an “item” indicating an item to be determined, and a reference value determined to be OK. It is a table which has a field of “reference value” and stores the reference value for each item when determining the degree of organization or risk.

  FIG. 3B shows an example of the rank determination table 123. As shown in FIG. 3B, the rank determination table 123 includes a “type” indicating a type (organization degree or degree of risk), a “rank” indicating a rank, and a “total evaluation point” indicating an overall evaluation point belonging to the rank. It is a table which has a field and stores a rank and a comprehensive evaluation score in association with each of the degree of organization and the degree of danger.

  The reference image database 124 is a database that stores reference images of desks, floors, and cabinets that are objects of safety and health determination. The reference image is an image obtained by capturing an image with no determination target placed. In each reference image, an image area of the determination target is specified in advance, and coordinate information of the image area is stored in association with the reference image. In addition, in the reference image of the cabinet, the actual dimension of the width of the cabinet is associated and stored.

  The captured image database 125 is a database for storing captured images captured by the camera 16.

The determination result database 126 is a database for storing determination result data of the safety and health degree determined based on each captured image stored in the captured image database 125.
FIG. 4 shows an example of data storage in the determination result database 126. As shown in FIG. 4, the determination result database 126 includes “image ID”, “determination target”, “item”, “reference value”, “measurement value”, “determination”, which indicate image identification information of a captured image. It has fields such as “difference” and “evaluation point”, and stores determination result data for each captured image. In FIG. 4, the determination result data regarding the degree of organization and order among the safety and health levels is shown, but the determination result data regarding the risk level is also stored in the same manner.

  The storage unit 12 further stores the sizes of A4 documents and pipe files.

  The communication unit 13 includes a LAN (Local Area Network) adapter, a router, and the like, and performs communication connection with an external device via a communication network such as a LAN to perform data transmission / reception.

  The display unit 14 is configured by an LCD (Liquid Crystal Display) or the like, and performs various displays according to a display control signal from the CPU 10.

  The operation unit 15 includes a cursor key, various function keys, and a shutter key. The operation unit 15 receives a pressing input of each key by the user and outputs operation information to the CPU 10. The operation unit 15 includes a touch panel or the like in which transparent electrodes are arranged in a grid so as to cover the surface of the display unit 14, detects a position pressed with a finger or a touch pen, and uses the position information as operation information. It outputs to CPU10.

  The camera 16 includes an imaging element such as a lens, a diaphragm, a CCD (Charge Coupled Device), or a CMOS (Complementary Metal Oxide Semiconductor), and forms an optical image of a subject on the imaging element, and uses the image as an electrical signal. This is imaging means for outputting to the CPU 10.

<Operation of Information Processing Apparatus 1>
Next, the operation in this embodiment will be described.

  FIG. 5 shows a flowchart of the safety and health level determination process executed by the information processing apparatus 1. The safety and health level determination process is executed by the cooperation of the CPU 10 and the safety and health level determination software 121 stored in the storage unit 12 when the operation unit 15 instructs the activation of the safety and health level determination software 121. Is done.

First, the CPU 10 determines whether data exists in the “reference value” field of the reference value data table 122 of the storage unit 12 (step S1).
When it is determined that there is no reference value data in the reference value data table 122 (step S1; NO), the CPU 10 activates the reference value registration module 121a (step S2), and from the operation unit 15 according to the reference value registration module 121a. The input reference value is stored in the reference value data table 122 (step S3). For example, the CPU 10 displays a reference value setting screen having an input field for a reference value range for each item (see FIG. 3A) on the ordering degree and the degree of danger on the display unit 14, and is input by the operation unit 15. The value is stored in the “reference value” field of the reference value data table 122.

When it is determined that the reference value data exists in the reference value data table 122 (step S1; YES), the CPU 10 determines whether data exists in the “total evaluation score” field of the rank determination table 123 of the storage unit 12. (Step S4).
When it is determined that there is no data in the “total evaluation score” field of the rank determination table 123 (step S4; NO), the CPU 10 activates the rank registration module 121b (step S5), and operates the operation unit according to the rank registration module 121b. The comprehensive evaluation score input from 15 is stored in the reference value data table 122 (step S6), and the process proceeds to step S7. For example, the CPU 10 displays on the display unit 14 a rank setting screen having an input field for the range of overall evaluation points for the respective ranks of the degree of organization and the degree of risk (see FIG. 3B), and is input by the operation unit 15. The value is stored in the “total evaluation score” field of the reference value data table 122.
When it is determined that there is data in the “total evaluation score” field of the rank determination table 123 (step S4; YES), the CPU 10 proceeds to the process of step S7.

  In step S7, the CPU 10 activates the camera control module 121c (step S7). When the user presses the shutter button of the operation unit 15 so that the lens of the camera 16 is directed to an area (determination target area) for which the health and safety level is to be determined, the CPU 10 causes the camera 16 to perform imaging according to the pressing operation of the shutter button. (Step S8), the obtained captured image is stored in the captured image database 125 of the storage unit 12 (Step S9).

Next, the CPU 10 performs a determination process on the captured image obtained by imaging (step S10).
FIG. 6 shows a flowchart of the determination process. The determination process is executed in cooperation with the CPU 10, the image comparison module 121d, and the measurement result totaling module 121e.

First, the CPU 10 activates the image comparison module 121d (step S101).
Next, the CPU 10 opens the captured image captured in step S8 of FIG. 5 (step S102), and executes extraction processing on the captured image (step S103). The extraction process is a process for extracting an image of the determination target object of the degree of order and order.
FIG. 7 shows a flowchart of the extraction process. The extraction process is executed in cooperation with the CPU 10 and the image comparison module 121d.

  In the extraction process, the CPU 10 first extracts an area of the same color as the desk of the reference image (desk) in the reference image database 124 from the captured image (step S1001). Note that the colors do not have to match completely, and a color within a predetermined range in a predetermined color space (for example, RGB) may be extracted from the desk color of the reference image.

Next, the CPU 10 determines whether or not a region having the same color as the desk of the reference image exists in the captured image based on the extraction result (step S1002).
If it is determined that a region having the same color as the desk of the reference image exists in the captured image (step S1002; YES), the CPU 10 determines whether or not the shape of the region extracted in step S1001 is similar to the shape of the desk of the reference image. Is determined (step S1003). For example, if the reference image is analyzed to extract a feature of the desk shape (for example, a rectangle, a rhombus, etc.), and the shape of the area of the same color as the desk in the captured image has the feature, it is similar. Judge that

  When it is determined that the shape of the region extracted in step S1001 is similar to the shape of the desk of the reference image (step S1003; YES), the CPU 10 extracts information indicating that the type of the extract is a desk, and extraction The coordinate information of the designated area is stored in the RAM 11 in association with it (step S1015), and the process proceeds to step S104 in FIG.

  On the other hand, when it is determined that there is no area of the same color as the desk area of the reference image in the captured image (step S1002; NO), or the shape of the same color is extracted, the shape of the reference image is not similar to the desk (Step S1003; NO), CPU10 transfers to the process of step S1004. In addition, when the desk in a captured image is not extracted by this process, it is possible to perform manual extraction by the process after step S1009.

  In step S1004, the CPU 10 extracts an area having the same color as the floor of the reference image (floor) from the captured image (step S1004). Note that the colors do not have to match completely, and colors within a predetermined range in a predetermined color space may be extracted from the floor color of the reference image.

Next, the CPU 10 determines whether or not a region having the same color as the floor of the reference image exists in the captured image based on the extraction result (step S1005).
When it is determined that a region having the same color as the floor of the reference image exists in the captured image (step S1005; YES), the CPU 10 indicates that the type of the extract is the floor and the coordinate information of the extracted region. Are stored in the RAM 11 in association with each other (step S1015), and the process proceeds to step S104 in FIG.

  On the other hand, when it is determined that the captured image does not have an area of the same color as the floor area of the reference image (step S1005; NO), the CPU 10 proceeds to the process of step S1006. If the floor in the captured image data is not extracted by this processing, manual extraction can be performed in the processing after step S1009.

  In step S1006, the CPU 10 extracts an area having the same color as the reference image (cabinet) from the captured image (step S1006). Note that the colors do not need to match completely, and colors within a predetermined range in a predetermined color space may be extracted from the cabinet color of the reference image.

Next, based on the extraction result, the CPU 10 determines whether or not a region having the same color as the reference image cabinet exists in the captured image (step S1007).
When it is determined that a region having the same color as the reference image cabinet exists in the captured image (step S1007; YES), the CPU 10 in the captured image has a shape similar to the shape of the reference image cabinet extracted in step S1007. It is determined whether or not (step S1008). For example, by analyzing the reference image and extracting the characteristics of the cabinet shape (for example, rectangle, rhombus, etc.), if the shape of the area of the same color as the area in the captured image has the characteristics, it is similar. Judge that

  When it is determined that the shape of the region extracted in step S1008 is similar to the shape of the cabinet of the reference image (step S1008; YES), the CPU 10 extracts information indicating that the type of extract is a cabinet, and extraction The coordinate information of the designated area is stored in the RAM 11 in association with it (step S1015), and the process proceeds to step S104 in FIG.

  On the other hand, when it is determined that there is no area of the same color as the cabinet area of the reference image in the captured image (step S1007; NO), or even if the same color area is extracted, the shape is similar to the cabinet area of the reference image. If it is determined that there is not (step S1008; NO), the CPU 10 proceeds to the process of step S1009. In addition, when the cabinet in a captured image is not extracted by this process, manual extraction can be performed by the process after step S1009.

  In step S1009, the CPU 10 displays the captured image on the display screen of the display unit 14 (step S1009). When the determination object on the display screen is touched (pressed) by the user's operation of the operation unit 15 (step S1010), the CPU 10 extracts the touched periphery in the captured image as the determination object area, and the area. Is highlighted and displayed (step S1011). For example, when a point on the screen is touched with a finger, a pen, or the like, the CPU 10 causes the same color as the touched point or a color region within the predetermined range in the predetermined color space (the touched point). Are extracted from the captured image. Then, the outline of the extracted area is highlighted with a predetermined color.

Next, the CPU 10 displays a selection screen for selecting the type of extract (desk, floor, cabinet, document (flat stacking, vertical placement)) on the display unit 14 (step S1012).
When a type other than a document is selected by the operation unit 15 (step S1013; NO), the CPU 10 associates information indicating the type of the selected extract with coordinate information of the extracted area in the RAM 11. (Step S1015), and the process proceeds to step S104 in FIG.

  On the other hand, when a document is selected as the type of extract by the operation unit 15 (step S1013; YES), the CPU 10 displays a selection screen for selecting a document size (A4 document, pipe file) on the display unit 14. (Step S1014). When the size of the document is selected by the operation unit 15, the CPU 10 stores information indicating the type and size of the selected extract and the coordinate information of the extracted area in the RAM 11 in association with each other (step S1015). Then, the process proceeds to step S104 in FIG.

  In step S104 of FIG. 6, the CPU 10 executes a measurement process (step S104). The measurement process is a process of measuring a predetermined item of the extract (image of the determination target) extracted from the captured image by the extraction process.

FIG. 8 shows a flowchart of the measurement process. The measurement process is executed in cooperation with the CPU 10 and the image comparison module 121d.
First, the CPU 10 determines whether or not to measure the space ratio based on the type of extract extracted from the captured image (step S1021). Specifically, when the type of the extract is a desk, a floor, or a cabinet, it is determined that the space ratio is measured. If the type of extract is a document, it is determined not to measure the percentage of space.

  When determining that the space ratio is not to be measured (step S1021; NO), the CPU 10 proceeds to the process of step S1024.

If it is determined that the space ratio is to be measured (step S1021; YES), the CPU 10 compares the reference image and the region extracted from the captured image, and estimates the free space (B) that should be in the extract (step). S1022).
For example, when the type of the extract is a desk, as shown in the reference image, the shape on the desk is a rectangle such as a rectangle or a rhombus, which is an empty space where the entire area should be. On the other hand, when an object is placed on the desk, the empty space of the desk in the captured image is not the entire square, but is an area where the part where the object is placed is missing. Therefore, when the type of the extract is a desk, in step S1022, for example, it is assumed that the desired empty space (B) is the entire rectangular area surrounded by the outline of the desk extracted from the captured image. Calculate the area. The same applies to the floor.
For example, when the type of extract is a cabinet, the width of the empty space on the cabinet is the entire upper end of the cabinet, as shown in the reference image. On the other hand, when an object is placed on the cabinet, the upper end of the cabinet may be hidden by the object and become discontinuous. Therefore, when the type of the extract is a cabinet, it is assumed that the desired empty space (B) corresponds to the entire upper end portion of the cabinet extracted from the captured image, and the length of the width is calculated.
The above is an example, and the present invention is not limited to this. Alternatively, a captured image may be displayed on the display unit 14 and the user may be allowed to designate an empty space that should be provided by the operation unit 15.

Next, the CPU 10 calculates the ratio (A / B) of the empty space (B) that should be in the extract from the captured image and the actual empty space (A) (step S1023), and proceeds to the processing of step S1024.
For example, when the type of the extract is a desk or a floor, the area of the extract area extracted by the extraction process can be calculated as an actual empty space (A). Also, for example, when the type of the extract is a cabinet, the width of the portion where the object is not placed among the upper ends of the extract extracted by the extraction process is calculated as the actual empty space (A). Can do.
The above is an example, and the present invention is not limited to this. Alternatively, the captured image may be displayed on the display unit 14 and the user may be caused to designate an actual empty space by the operation unit 15.

  In step S1024, the CPU 10 determines whether or not to measure dimensions based on the type of extract. Specifically, when the type of the extract is a cabinet or a document, it is determined that the dimension is measured. If the type of extract is desk or floor, it is determined not to measure the dimensions.

  When determining that the dimension is not measured (step S1024; NO), the CPU 10 stores the calculated measurement value in the RAM 11 in association with the item name and the information stored in the RAM 11 in the extraction process, and in step S105 of FIG. Transition to processing.

  When it is determined that the dimension is to be measured (step S1024; YES), the CPU 10 determines whether or not the type of the extract is a cabinet (step S1025).

If it is determined that the type of extract is a cabinet (step S1025; YES), the CPU 10 measures the length (a) of the width of the cabinet extracted from the captured image (step S1026).
Next, the CPU 10 acquires the actual size (b) of the width of the reference image cabinet registered in the reference image database 124, and calculates the image ratio (c = a / b) (step S1027).

Next, the CPU 10 extracts the region of the luggage on the cabinet extracted from the captured image, and measures the dimension of the luggage protruding from the cabinet and the dimension (d) of the luggage height in the captured image (step S1028).
Then, the CPU 10 calculates the actual dimension (d × c) of the protruding width of the luggage and the height of the luggage from the ratio (c) and the dimension (d) of the image (step S1029), and uses the calculated measurement value as the item name. Then, it is stored in the RAM 11 in association with the information extracted in the extraction process (step S1034), and the process proceeds to step S105 in FIG.

  On the other hand, when determining that the type of the extract is a document (step S1025; NO), the CPU 10 measures the size (a1) of the document extracted from the captured image (step S1030). For example, when the documents extracted from the captured image are stacked, the CPU 10 measures the dimension of the length in the horizontal direction of the document extracted from the captured image. When the document extracted from the captured image is placed vertically, the length dimension of the document extracted from the captured image is measured.

Next, the CPU 10 obtains the length (here, the length of the long side) (b1) of the document having the size selected in step S1014 in FIG. 7 from the storage unit 12, and the image ratio (c1 = a1 / b1) is calculated (step S1031).
Next, the CPU 10 measures the height dimension (d1) of the document extracted from the captured image (step S1032).

  Then, the CPU 10 calculates the actual height (d1 × c1) of the document height from the image ratio (c1) and the size (d1) (step S1033), and uses the calculated measurement value by the item name and extraction processing. The information is stored in the RAM 11 in association with the extracted information (step S1034), and the process proceeds to step S105 in FIG.

  In step S105 of FIG. 6, the CPU 10 activates the measurement result totaling module 121e (step S105), acquires the reference value of the measurement result item stored in the RAM 11 from the reference value data table 122, and displays the measurement result. Comparison with the reference value (step S106).

As a result of the comparison, when it is determined that the measurement result is within the range of the reference value (step S107; YES), the CPU 10 determines that it is OK (step S108), and proceeds to the process of step S110.
As a result of the comparison, if it is determined that the measurement result is out of the reference value range (step S107; NO), it is determined that the measurement result is NG (step S109), and the process proceeds to step S110.

In step S110, CPU10 calculates the evaluation score of each measured item (step S110). The evaluation score can be calculated by the following (Formula 1). This evaluation point is a value that quantitatively indicates the degree of organization or risk of the corresponding item of the extracted determination object.
Evaluation point = determination flag × (absolute value of difference between measured value and reference value) (Equation 1)
Here, the determination flag is +1 if the determination is OK, and -1 if the determination is NG.

Next, the CPU 10 determines whether there are other determination objects (step S111). For example, the CPU 10 displays a message for inquiring of the user whether there is another determination target object on the display unit 14, and determines whether there is another determination target object according to the operation from the operation unit 15. . For example, it is preferable to display a captured image on the display unit 14 so that the user can recognize which region has been determined by adding a predetermined color to the already extracted determination target.
If it is determined that there is another determination target (step S111; YES), the CPU 10 returns to the process of step S103. Note that, in the extraction process, duplicated extraction is not performed on the determination target that has been extracted once.

  When it is determined that there are no other determination objects (step S111; NO), the CPU 10 adds the evaluation points of the degree of order and the degree of risk calculated from each of the objects to be determined, respectively. Each comprehensive evaluation score is calculated (step S112). The comprehensive evaluation score is a value that quantitatively indicates the overall degree of organization and risk of the determination target area captured by the captured image. In the calculation of the overall evaluation score, when there are multiple evaluation points for one item (for example, when there are multiple desks in the captured image), the average score of the evaluation points for that item is calculated. And it is good also as an evaluation point of the item.

  Then, the CPU 10 reads the rank determination table 123 of the storage unit 12 and compares the calculated overall evaluation score with the range of the overall evaluation score of each rank for each of the degree of organization and the degree of risk, and the comparison result is obtained. Based on the rank of the comprehensive evaluation point (step S113), the process proceeds to step S11 in FIG.

  In step S11 of FIG. 5, the CPU 10 activates the determination result output module 121f (step S11), displays the determination result screen 141 on the display unit 14 (step S12), and ends the safety and health degree determination process.

FIG. 9 shows an example of the determination result screen 141 displayed on the display unit 14.
As shown in FIG. 9, the determination result screen 141 includes a comprehensive result display column 141 a that displays a comprehensive evaluation score and a rank for each of the degree of order and risk, a reference value for each item of each determination object, A detailed result display column 141b for displaying a list of measured values, determinations, differences, and evaluation points is provided. FIG. 9 shows the result when there is no risk judgment object (cabinet) in the judgment target area, but when the risk is judged, the judgment result is also displayed.

  As described above, according to the safety and health level determination processing, an algorithm in which the degree of arrangement and the degree of risk of a determination target object such as a desk, a floor, a cabinet, and a document in the determination area are determined in advance from the captured image of the determination target area. Since it is automatically calculated (determined) and output, the quantitative safety and health level can be obtained with a unified standard. In addition, since the degree of organization and risk is calculated simply by imaging the determination target area, it is possible to efficiently perform the safety and health patrol work with a small number of people.

As described above, according to the information processing apparatus 1 in the present embodiment, the CPU 10 extracts and extracts the image of the determination target object of the degree of organization and order from the captured image of the determination target area captured by the camera 16. The value of a predetermined item is measured from the image of the determination target, the degree of ordering of the determination target is determined based on the measurement result and the reference value, and the determination result is displayed on the display unit 14.
Accordingly, since the degree of organization and order in the judgment area can be automatically calculated (determined) from the captured image of the judgment target area, it is not necessary to determine the degree of organization and order by a person, and the work of determining the degree of organization and order is performed. Can be performed efficiently with a small number of people. In addition, it is possible to calculate a quantitative order and tidy degree based on a unified standard.

  Further, when a plurality of determination objects are included in the captured image, the CPU 10 comprehensively organizes the areas imaged by the camera 16 based on values obtained by calculating the order and arrangement degree of the plurality of determination objects. Determine the degree of order. Therefore, it is possible to efficiently perform not only the degree of individual arrangement and order of the determination target object, but also the total degree of arrangement of the determination target area captured by the camera 16.

  Specifically, the information processing apparatus 1 can determine the degree of organization of desks, floors, cabinets, and documents. When the determination target is a desk, the proportion of the desk space can be measured, and the degree of organization can be determined based on the measurement result. When the determination target is a floor, the proportion of space on the floor can be measured, and the degree of organization can be determined based on the measurement result. When the determination target is a cabinet, the proportion of space on the cabinet can be measured, and the degree of organization can be determined based on the measurement result. When the determination target is a document, the height of the document can be measured, and the degree of organization can be determined based on the measurement result.

In addition, the CPU 10 further extracts an image of the risk determination target object from the captured image captured by the camera 16 and measures a predetermined risk determination item value from the risk determination target image. Based on the measurement result, the degree of risk of the determination object is determined.
Therefore, since the risk level can be automatically calculated (determined) from the captured image of the determination target object, it is not necessary to determine the risk level by a person, and the risk level determination work can be efficiently performed with a small number of people. Can be done. Further, it is possible to calculate a quantitative risk level based on a unified standard.

  In addition, the description content in the said embodiment is a suitable example of an information processing apparatus, and is not limited to this.

  For example, in the above-described embodiment, it has been described that the output unit is the display unit 14 and the determination result is displayed on the screen of the display unit 14. However, the present invention is not limited to this. For example, the determination result is output to a printer or the like. It is good also as outputting as printed matter from.

  In the above-described embodiment, the case in which the determination target is a desk, a floor, a cabinet, or a document has been described as an example. However, the present invention is not limited to this. Further, items for determining the degree of order and order and the degree of danger are also shown as a preferable example, and the present invention is not limited to this.

  In the above embodiment, the information processing apparatus 1 has been described as a mobile terminal. However, for example, the information processing apparatus 1 may be installed at a position where the determination target area can be imaged. When there are a plurality of determination target areas, the determination result may be transmitted to the server device and the determination result may be output from the server device.

  Also, as a computer-readable medium storing a program for executing each of the above processes, a non-volatile memory such as a flash memory, a portable recording medium such as a CD-ROM, in addition to a ROM, a hard disk, etc. Is also possible. A carrier wave is also used as a medium for providing program data via a predetermined communication line.

  In addition, the detailed configuration and detailed operation of each device constituting the information processing apparatus can be changed as appropriate without departing from the spirit of the invention.

(Appendix)
Although several embodiments of the present invention have been described, the scope of the present invention is not limited to the above-described embodiments, but includes the scope of the invention described in the claims and equivalents thereof.
The invention described in the scope of claims attached to the application of this application will be added below. The item numbers of the claims described in the appendix are as set forth in the claims attached to the application of this application.
<Claim 1>
Imaging means;
Extraction means for extracting an image of a determination target of the degree of order and order from a captured image captured by the imaging means;
Measuring means for measuring the value of a predetermined item from the image of the determination object extracted by the extracting means;
Based on the measurement result by the measurement means, a determination means for determining the degree of organization of the determination object,
An output means for outputting a determination result by the determination means;
An information processing apparatus comprising:
<Claim 2>
The information processing apparatus according to claim 1, wherein the determination unit determines a degree of organization of the determination target based on a measurement result obtained by the measurement unit and a reference value of the predetermined item.
<Claim 3>
In the case where a plurality of determination objects are included in the captured image, the determination unit is configured to calculate a total of areas captured by the imaging unit based on a value obtained by calculating a degree of ordering of the plurality of determination objects. The information processing apparatus according to claim 1, wherein a general organization degree is determined.
<Claim 4>
The information processing apparatus according to claim 1, wherein the determination target includes at least one of a desk, a floor, a cabinet, and a document.
<Claim 5>
The predetermined item includes a ratio of space on the desk when the determination target is a desk, and includes a ratio of space on the floor when the determination target is a floor, and the determination target is a cabinet. The information processing apparatus according to claim 4, wherein the information processing apparatus includes a ratio of a space on the cabinet, and includes a height of the document when the determination target is a document.
<Claim 6>
The extraction unit further extracts an image of the risk determination target object from the captured image captured by the imaging unit,
The measuring means further measures a value of a predetermined risk determination item from an image of the risk determination target object,
The information processing apparatus according to any one of claims 1 to 5, wherein the determination unit determines a risk level of the risk determination target object based on a measurement result of a value of the risk level determination item.
<Claim 7>
The risk determination target is a cabinet,
The information processing apparatus according to claim 6, wherein the predetermined risk determination item includes at least one of a protruding width of the luggage from the cabinet, a height of the luggage on the cabinet, and a ratio of a space on the cabinet.
<Claim 8>
Imaging with imaging means;
Extracting an image of a determination target of the degree of order and arrangement from a captured image captured by the imaging unit;
Measuring a value of a predetermined item from the extracted image of the determination object;
A step of determining a degree of organization of the determination object based on the measurement result;
Outputting the determination result;
A method for determining the degree of order and order.
<Claim 9>
A computer used in an information processing apparatus including an imaging unit,
Extraction means for extracting an image of a determination target of the degree of order and order from a captured image captured by the imaging means;
Measuring means for measuring a value of a predetermined item from the image of the determination object extracted by the extracting means;
A determination unit for determining a degree of organization of the determination target based on a measurement result by the measurement unit;
Output means for outputting a determination result by the determination means;
Program to function as.

1 Information processing apparatus 10 CPU
11 RAM
12 storage unit 121 safety and health degree determination software 121a reference value registration module 121b rank registration module 121c camera control module 121d image comparison module 121e measurement result totaling module 121f determination result output module 122 reference value data table 123 rank determination table 124 reference image database 125 captured image database 126 determination result database 13 communication unit 14 display unit 15 operation unit 16 camera

Claims (9)

Imaging means;
Extraction means for extracting an image of a determination target of the degree of order and order from a captured image captured by the imaging means;
Measuring means for measuring the value of a predetermined item from the image of the determination object extracted by the extracting means;
Based on the measurement result by the measurement means, a determination means for determining the degree of organization of the determination object,
An output means for outputting a determination result by the determination means;
An information processing apparatus comprising:   The information processing apparatus according to claim 1, wherein the determination unit determines a degree of organization of the determination target based on a measurement result obtained by the measurement unit and a reference value of the predetermined item.   In the case where a plurality of determination objects are included in the captured image, the determination unit is configured to calculate a total of areas captured by the imaging unit based on a value obtained by calculating a degree of ordering of the plurality of determination objects. The information processing apparatus according to claim 1, wherein a general organization degree is determined.   The information processing apparatus according to claim 1, wherein the determination target includes at least one of a desk, a floor, a cabinet, and a document.   The predetermined item includes a ratio of space on the desk when the determination target is a desk, and includes a ratio of space on the floor when the determination target is a floor, and the determination target is a cabinet. The information processing apparatus according to claim 4, wherein the information processing apparatus includes a ratio of a space on the cabinet, and includes a height of the document when the determination target is a document. The extraction unit further extracts an image of the risk determination target object from the captured image captured by the imaging unit,
The measuring means further measures a value of a predetermined risk determination item from an image of the risk determination target object,
The information processing apparatus according to any one of claims 1 to 5, wherein the determination unit determines a risk level of the risk determination target object based on a measurement result of a value of the risk level determination item. The risk determination target is a cabinet,
The information processing apparatus according to claim 6, wherein the predetermined risk determination item includes at least one of a protruding width of the luggage from the cabinet, a height of the luggage on the cabinet, and a ratio of a space on the cabinet. Imaging with imaging means;
Extracting an image of a determination target of the degree of order and arrangement from a captured image captured by the imaging unit;
Measuring a value of a predetermined item from the extracted image of the determination object;
A step of determining a degree of organization of the determination object based on the measurement result;
Outputting the determination result;
A method for determining the degree of order and order. A computer used in an information processing apparatus including an imaging unit,
Extraction means for extracting an image of a determination target of the degree of order and order from a captured image captured by the imaging means;
Measuring means for measuring a value of a predetermined item from the image of the determination object extracted by the extracting means;
A determination unit for determining a degree of organization of the determination target based on a measurement result by the measurement unit;
Output means for outputting a determination result by the determination means;
Program to function as.

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