JP2019138831A - Color index value acquisition system, and color index value acquisition method - Google Patents

Abstract

To provide a color index value acquisition system that can smoothly implement a measurement cancel operation, and enable achievement of efficient works.SOLUTION: The present color index value acquisition system comprises a color index value control device 50. The color index value control device comprises: a color index value calculation unit 51 that calculates a color index value on the basis of photographing images acquired from measurement terminals 1a and 1b; an output control unit 52 that vocally outputs the color index value from a portable terminal 2 carried by a measurer; a cancel determination unit 54 that determines whether a cancel signal indicative of non-implementation of registration of the color index value is acquired from the measurement terminals 1a and 1b; and a registration control unit 55 that controls the registration of the color index value. The registration control unit 55 is configured to, when the cancel determination unit 54 determines that the cancel signal is acquired, delete the color index value without registering it.SELECTED DRAWING: Figure 16

Description

  The present invention relates to a color index value acquisition system and a color index value acquisition method for acquiring a color index value serving as a reference for judging the growth status of plants, particularly crops, by color.

  In agriculture, especially rice cultivation, a leaf color scale, which is a color sample of leaf color concentration, which is an index for fertilization management of paddy rice, may be used. In the leaf color scale, the leaf color is shown stepwise from the lightest 1 to the darkest 7. The leaf color can be measured in 13 steps by reading up to an intermediate value of each value. The leaf color scale can measure the leaf color easily, but there is a problem that the measurement results vary depending on the time of day (the position of the sun) and the difference in external light depending on the weather. There is also a problem that the measurement results vary depending on the experience and skill of the measurer.

  Based on such a problem, for example, a plant information acquisition system is known that can calculate a value indicating the chlorophyll content of a plant based on image data obtained by imaging the plant (see Patent Document 1).

JP 2016-127806 A

  As described above, the plant information acquisition system disclosed in Patent Document 1 can calculate the value of the chlorophyll content based on the captured image. However, when the measurer determines that the measurement (image shooting) is to be performed again at the timing when the image data is transmitted from the plant information acquisition device, which is a camera, to the portable information terminal, the plant information acquisition device cancels the measurement. For example, if the measurer is working with the portable terminal in his / her pocket, etc., he / she must operate the portable terminal after taking it out. There was a problem.

  The present invention has been made in view of the above circumstances, and provides a color index value acquisition system and a color index value acquisition method capable of smoothly executing a measurement cancel operation and realizing efficient work. The purpose is to do.

In order to solve the above-described problem, the color index value acquisition system of the present invention includes:
A color index value acquisition system comprising: a measurement terminal that images a measurement object; and a color index value control device that is communicably connected to the measurement terminal,
The color index value control device includes:
A color index value calculation unit that calculates a color index value based on a captured image acquired from the measurement terminal;
An output control unit for outputting a voice from a mobile terminal possessed by the measurer with the color index value;
A cancel determination unit that determines whether or not a cancel signal indicating that registration of a measurement result is not performed is acquired from the measurement terminal;
A registration control unit that controls registration of the color index value;
The registration control unit deletes the color index value without registering when the cancel determination unit determines that the cancel signal has been acquired.

Further, the color index value acquisition method of the present invention includes:
A color index value acquisition method using a measurement terminal that captures an image of a measurement object and a color index value control device that is communicably connected to the measurement terminal,
A calculation step in which a color index value calculation unit calculates a color index value based on a captured image acquired from the measurement terminal;
An output control step, wherein the output control step outputs sound from a portable terminal possessed by the measurer with the color index value;
A cancellation determination step for determining whether or not the cancellation determination unit has acquired a cancellation signal indicating that registration of measurement results is not performed from the measurement terminal;
A registration control unit comprising a registration control step for controlling registration of the color index value;
In the registration control step, when it is determined that the cancel signal is acquired in the cancel determination step, the color index value is deleted without being registered.

  According to the configuration as described above, a voice that reads out the color index value is output from the mobile terminal, and the color index value control device does not register the color index value when the cancel signal is acquired from the measurement terminal. Deleted. For this reason, the measurer can redo the imaging without visually recognizing or operating the mobile terminal. Thereby, work can be made efficient.

  According to the present invention, it is possible to provide a color index value acquisition system and a color index value acquisition method that can smoothly execute a measurement cancel operation and enable efficient work.

1 is a block diagram illustrating a color index value calculation system according to Embodiment 1. FIG. It is a figure which shows the example of the data registered into a farmland information database. It is a figure which shows the example of the data registered into a measurement point database. It is a figure which shows the example of the data registered into a color measurement value database. It is a figure which shows the example of the data registered into a growth target database. It is a figure which shows the example of the data registered into a color scale database, and the example of the expression system of a color scale. It is a figure which shows the example of a display of a smart phone when calculating a color index value from a picked-up image. It is a flowchart for demonstrating the setting process of a color scale. It is a graph which shows the relationship between a color index value and a color value when the number of color samples is equal to or greater than the number of steps of the color scale to be created. It is a graph which shows the relationship between a color index value and a color value when the number of color samples is two. It is a graph which shows the case where the number of color samples is three or more and the relationship between the color index value and the color value is approximated by a logarithmic curve. 6 is a graph showing a relationship between a color index value and a color value when the number of color samples is three or more. It is a figure for demonstrating the preparation method of the color conversion type | formula using the existing color scale. It is a figure which shows the result of the regression analysis using the data shown in FIG. It is a figure for demonstrating the preparation method of the color conversion type | formula using the image data which image | photographed actual crops. 6 is a block diagram illustrating a configuration of a mobile terminal according to Embodiment 2. FIG. 4 is a flowchart for explaining an operation performed by the color index value control apparatus. 4 is a flowchart for explaining display information generation processing by an output control unit of the color index value control apparatus. It is the figure which showed the example of the display information which an output control part produces | generates similarly. It is the figure which showed another example of the display information which an output control part produces | generates similarly. It is the figure which showed another example of the display information which an output control part produces | generates similarly. It is the figure which showed another example of the display information which an output control part produces | generates similarly. It is the figure which showed another example of the display information which an output control part produces | generates similarly. It is the figure which showed another example of the display information which an output control part produces | generates similarly. It is a figure which shows the external appearance of a measurement terminal, (a) is the figure seen from the front, (b) is the figure seen from the upper surface, (c) is the figure seen from the left. It is the figure seen from the front similarly and is a figure which shows the state in which the head part is open. FIG.

Embodiment 1 FIG.
The first embodiment will be described below.
The color index value calculation system and the color index value calculation method according to the first embodiment calculate a color index value that is a standard for the growth state from the colors of leaves and fruits that are predetermined parts of various crops as a predetermined plant. . The color index value is used, for example, to determine the harvesting time from the color of the fruit, and enables an agricultural worker who is not skilled in cultivation of the fruit to harvest at the optimum time. . In fruit harvesting, fruits before ripe are often harvested, making it difficult to determine the harvest time. Further, since the climate varies depending on the year, the harvest time also varies depending on the year, and it is necessary to determine the harvest time by actually judging the growth situation, and the color index value can be used as the judgment material. In addition, it is possible to discuss the color index value as a common recognition item when discussing the growth situation between farmers, and the color index value of that field is better than the color index value of this field. It is possible to indicate that the value is low and the growth is delayed by numerical values rather than expressions of ambiguous colors such as dark and light, blue and red. In addition, the growth status not only represents the fruit harvest time with the color index value of the fruit color, but also represents the growth status of each stage until harvesting on the leaves, stems and other parts in addition to the fruit. Become.

  For example, it can be used as a color index value and a judgment material such as whether the growth state is good or bad from the cultivation period, whether it is late or early, poor growth or overgrowth. For example, the color index value is set so that the value increases in accordance with the change of the color value with time, and each value is linked to the cultivation period. When 5 is associated as the color index value at the time of the month, if the color index value is 4 at this time, it can be determined that the growth is delayed or the growth is poor. It has become. Conversely, when the color index value at this time is 6, it can be determined that the growth is progressing or it can be determined that the growth is excessive.

  As shown in FIG. 1, the color index value calculation system in the present embodiment is a smartphone as a mobile terminal in which a digital camera 1a or digital camera 1b as a color measuring unit and digital cameras 1a and 1b are connected wirelessly or by wire. 2, a server (data management server 20) capable of data communication via the smartphone 2 and the Internet 30, and a personal computer 10 capable of data communication via the data management server 20 and the smartphone 2 via the Internet 30. The personal computer 10 also functions as various servers and may be expressed as a server, or may be a part of the server 20, for example, one that is connected to the server 20 and functions as a terminal. The personal computer 10 is installed in a place where there is an agricultural and forestry-related organization such as an agricultural cooperative or various agricultural and forestry test sites, and is used by those who are related to these organizations.

  In the present embodiment, there are two types of digital cameras 1a and 1b. The first type of digital camera 1a is mainly for photographing leaves, and the second type of digital camera 1b is mainly used. This is for photographing fruits such as fruits. Each of these cameras 1a and 1b is configured to photograph a plant with a dedicated light source (LED) while blocking outside light, and prevents the color from changing due to the influence of outside light during photographing. . In the digital camera 1a mainly for photographing the leaves, the photographing is performed with the leaves sandwiched, and by placing the leaves, the leaves are placed on the object side end of the lens barrel containing the photographing lens. In this case, photographing is performed while preventing the entry of external light, and it is used for color measurement of a thin part such as a leaf. It is also possible to take a picture with the color sample portion of the color scale in between. That is, the digital camera 1a can photograph a thin and flexible member.

  The second type of digital camera 1b can shoot in a state in which the entry of external light is prevented by pressing the object side of the lens barrel against the subject for shooting. Since the digital camera 1b is used by being pressed against a subject, it is difficult to photograph a flexible subject without pressing it from behind, but it is suitable for photographing a relatively hard subject such as a fruit. . These digital cameras 1a and 1b can photograph a predetermined part of a predetermined plant as a subject while suppressing the influence of external light as much as possible. The photographing range is a small range, and for example, an average of color values photographed by a sensor portion in a predetermined range excluding a peripheral portion of the photographing range is set as a color value of a predetermined part of a predetermined plant. The outside range is, for example, a range of 2 mm × 2 mm on the subject and a range of 200 pixels × 200 pixels on the image sensor. In the image sensor, for example, RGB color filters are used, and in the digital cameras 1a and 1b, the above-mentioned predetermined ranges of the respective colors of red (R), green (G), and blue (B) are synchronized and processed. Frame information is output. The color value is not limited to the RGB value, and a color system of another color space may be used, for example, XYZ may be used. Further, a luminance value calculated from RGB or the like may be used. In addition, the color space system that can be used may be any color system, for example, HSV, HLS, YUV, YCbCr, YPbPr, or the like. Image data of 200 pixels × 200 pixels is output from the digital cameras 1 a and 1 b to the smartphone 2. In the image data output to the smartphone 2, the RGB value of each pixel of the image data in the predetermined range described above is averaged to calculate one RGB value, and this RGB value is converted into a color index value using a color conversion formula. To do. Then, the color index value is displayed on the display of the smartphone 2.

  In the smartphone 2, a color index value calculation application (dedicated application A) that performs the above-described processing is installed and can be activated. The color index value calculation application calculates a color index value when image data is input from the digital cameras 1a and 1b, and inputs an input date and time (color measurement date and time) of image data by a clock function, and GPS The position is input by the position measurement function. The color index value, the date and time of acquisition of the color value for the color index value, and information on the acquisition position of the color value are transmitted from the smartphone 2 to the data management server 20 via the Internet 30.

  The data management server 20 is a user information DB in which information for identifying a user such as account information including an ID (customer ID) and a password is registered, and information about the user including other addresses and contact information is registered. (Database) 21, farmland information DB 22 in which information about farmland such as a position and address indicating the range of the farmland where the color index value is calculated by the color index value calculation system is registered, date, etc. The growth target DB (growth information storage unit) 23 in which color index values that are targets of various crops are registered in association with the period that is represented by the period, and the color index values of the above-mentioned farmland were measured. A measurement point DB 24 in which measurement points as positions are registered and a predetermined color system read from images taken by the digital cameras 1a and 1b. A color measurement value DB 25 registered by associating a color measurement value (color index value) obtained by converting the value of the measured color with a color conversion formula in association with the user who transmitted the measurement value, the measured farmland, the measurement point, and the measurement date and time; A color scale DB 26 that registers color conversion formulas for calculating color index values from measured values in association with regions and types of crops, and a dedicated application A that is a program related to a color index value calculation system that operates on the smartphone 2 are registered. The application storage unit 27 and the control unit 28 are provided. When crops are photographed by the digital cameras 1a and 1b, color system values such as RGB values are extracted from the photographed images, and the extracted values are converted by a color conversion formula to obtain a color that is a color index value. The measured value is displayed on the display of the smartphone 2.

  The user information DB 21 includes information related to an account for the user to access the data management server 20, information on contact information to the user such as name, address, e-mail address, telephone number, etc. Personal information such as information such as sex, information such as the address of the farmland that is owned or used, and information related to charging when the service of the color index value calculation system has a paid service are registered.

  In the farmland information DB 22, as shown in the chart of FIG. 2, a serial number for each stroke of farmland is associated with the user ID of the user. , The field name for each brushstroke, the address by the lot number and the residence display for each brushstroke, the regional information that is the name that mainly indicates the crop production area, the area of the farmland for each brushstroke, and the apex of the shape of the farmland for each stroke The number of shape vertices as the number of each, the coordinates of each vertex that is the coordinates of each vertex of the farmland for each stroke, the name of the owner of the farmland, and whether or not there is a usage fee for the farmland are registered. The area information is, for example, a name indicating the area, but does not necessarily match the address, and is an area name used for the crop production area. A brush is a unit of land that is registered as one land in the real estate registry, and is basically a lump of land owned by the same owner. The lot number is a number that is assigned to each brush and indicates the address. is there. In addition, the serial number of each brush. If the land of each brush can be distinguished in each customer ID, it may not be uniquely determined, but may be uniquely determined. The number of shape vertices is 3 for a triangular land, 4 for a quadrangular land, and 5 for a pentagonal land. In this embodiment, the vertex coordinates are coordinates of a geodetic system represented by latitude and longitude measured by GPS of the vertex of the shape of a single stroke of land. The vertex coordinates are input by the user from the smartphone 2 to the farmland information DB 22 of the data management server 20. When the information on the land owned or used by the user is registered, the smartphone uses the smartphone at the vertex of the land shape. 2, the latitude and longitude are measured and input using the dedicated application A. When the latitude / longitude of the vertex position is known in advance, the latitude / longitude may be input as a numerical value to the farmland information DB 22 without measurement.

  As shown in the chart of FIG. 3, the measurement point DB 24 includes the user ID of the user and the serial number for each brush of the farmland. And the latitude and longitude of the measurement point measured in association with the field name. Further, the number of measurement points is registered for each brush, and the latitude and longitude of the measurement points are registered by this number. Note that the latitude and longitude at the measurement point are the latitude and longitude measured by the positioning device such as the GPS sensor of the smartphone 2 by the dedicated application A on the smartphone 2 connected to the digital cameras 1a and 1b when measuring the color measurement value. The data is output and registered in the data for transmission to the data management server 20, transmitted, and registered in the measurement point DB 24. When inputting the position of the measurement point, each measurement point is assigned a number, for example, a measurement point No. which is a number indicating the measurement order. Is attached and each measurement point is assigned a serial number for each brush. Or the field name and measurement point No. It can be specified with.

As shown in the chart of FIG. 4, the color measurement value DB 25 is associated with the customer ID, the field name (or serial number), and the names of crops such as rice, apples, eggplants and mandarin oranges cultivated on the farmland, Koshihikari, etc. And the above-mentioned measurement point No. In addition, a GPS measurement location, a shooting date and time, and a color measurement value as a color index value are registered.
In the measurement of the color index value, it is preferable to perform the measurement a plurality of times at one measurement point. For example, a plurality of measurements are performed by sequentially measuring nearby fruits in the case of fruits. The color measurement value may be a representative value such as an average value of a plurality of measurement values at the same measurement point (range in the vicinity). Further, since position measurement by GPS is performed every time the color index value is measured, it is preferable to obtain representative values such as average values for the measured latitude and longitude. In addition, the shooting date and time may use an average value, a start date and time, or an end date and time in consideration of time lapse due to multiple measurements.

The growth target DB 23 is set for each crop in each region, and a color index value (color measurement value) target value for each period represented by a date is registered, and a color index indicating the growth of the crop It is possible to determine whether the value is a target value at the time of measurement, or whether the color index value is lower or higher than the target value. In addition, when the color index value is substantially the same as the target value, it indicates that it is growing smoothly, when the color index value is lower than the target value, it indicates that the growth is delayed, and the color index value is lower than the target value. If it is high, it indicates that the growth is fast.
For example, as shown in FIG. 5, the growth target DB 23 has a time axis (X axis) based on the type of crop, for example, the name of a crop such as an apple or a tangerine, a variety such as an apple or a tangerine, and a region. , Data representing a graph represented by an index value axis (Y axis: color index value axis) is registered. The region indicates a range to which the target value is applied. For example, the region is a name indicating a region set by an organization such as an agricultural test site or an agricultural cooperative that sets the target value.

  As shown in FIG. 6, the color scale DB 26 is a color conversion formula for converting color values extracted from images photographed by the digital cameras 1 a and 1 b into color index values (color measurement values) or for conversion. A data table is stored. The data table for color conversion is calculated from the color conversion formula, and is used for reading out the color index value corresponding to the color value on the data table that most closely approximates the color value extracted from the photographed image. It is. In the color scale DB 26, an expression method and a color conversion data table or a color conversion equation are registered in association with the crop name and the variety. Here, the expression method indicates how to obtain a color conversion formula when converting a color value such as an RGB value into a color measurement value. In the present embodiment, the expression method No. 1 is an image obtained by photographing a color scale as an existing color sample, for example, RGB values when colors such as RGB values are represented by three values, luminance values obtained from RGB values, other values, and the like. A color conversion equation is obtained by multiple regression analysis using a plurality of types of values. In this case, a relationship between a color index value that is a numerical value assigned to each color sample and a color value extracted from an image obtained by photographing the color sample is obtained.

  In this case, it is premised that there is a color scale as a color sample, and the color index value can be output as digital data by photographing with the digital cameras 1a and 1b from a method of comparing the color scale with the sample and determining the color index value. The purpose is to do so. In addition, there is a correlation between values that can be measured other than color, for example, the concentration of a predetermined organic substance or inorganic substance such as sugar content, starch concentration, and various acid concentrations, the concentration of a measurable substance, and the growth of crops. If this is recognized, this is used as the color index value, and the color index value and color value are measured for the same sample (agricultural product as a sample), and multiple regression analysis is performed using these values. A color conversion formula for converting the value of the color to a color index value may be obtained. The color index value itself may be set in any way, but it is necessary to make it a value that correlates with the growth state of the crop, for example, the degree of maturity of the harvest such as fruits. For example, the color index value at the time when the fruit is generated is set to 0, the actual harvesting time or the ripe time after the harvesting time is set to 10, and the standard period from the generation of the fruit to the ripeness is divided at equal intervals. A number between 1 and 10 may be assigned, and a color index value corresponding to the measured time may be assigned to the measured color value, and various regression analyzes may be performed using this as a sample value.

  Expression method no. 1, when a color conversion formula is obtained by using RGB values for multiple regression analysis, C is a color measurement value (color index value), RGB values are R, G, B, R, G , B are r, g, and b, and the constant is k. The color conversion equation is expressed as C = r * R + g * G + b * B + k.

Expression method no. 2 divides the above color conversion formula into two by a specific color measurement value, for example, 1 when the minimum value of the color measurement value is 1, the maximum value is y, and the specific color measurement value is x. Are divided into color conversion formulas up to x and color conversion formulas from x to y, and two color conversion formulas are used. For example, the color index when the color change is slow relative to the growth rate when it is immature, and the color change is slow relative to the growth rate immediately before ripening, or vice versa. Two color conversion formulas may be used by dividing into a value range and a color index value range at an early stage of color change. In this case as well, the calculation using the color conversion formula is, for example, an expression scheme No. 1 can be performed.
Expression method no. The number of color conversion formulas in 2 is two. The first color conversion formula is that R, G, and B are R, G, and B coefficients, and R1, G1, and B are R, G1, and B coefficients. The color conversion formula with the term k1 is represented by C = r1 * R + g1 * G + b1 * B + k1. The second color conversion formula is R, G, B for RGB values, r2, g2, b2 for R, G, B coefficients, and k2 for a constant term. = R2 * R + g2 * G + b2 * B + k2.

  Expression method no. For example, luminance value is calculated from RGB values as, for example, one variable (independent variable), one variable is obtained, and a color conversion equation is obtained by linear regression analysis (single regression analysis). The color conversion formula 3 is C = y * Y + k, where C is the color measurement value, Y is the luminance, y is the coefficient of Y, and k is the constant term.

Expression method no. 4 is for approximating a curve using polynomial approximation (for example, curve regression analysis).
Expression method no. For example, the color conversion formula in FIG. 4 is a method for calculating a luminance value as, for example, one variable (independent variable) from RGB values, obtaining one variable, and obtaining a color conversion formula by curve regression analysis. . The color conversion equation of 4 is such that C = y1 * Y ^ 2 + y2 when the measured color value is C, the luminance is Y, the coefficient of Y ^ 2 is y1, the coefficient of Y is y2, and the constant term is k. * Y + K.
Expression method no. 5 is a polynomial having a cubic or higher order by curve regression analysis (high-order regression analysis). The color conversion formula of 5 is such that C = a * Y ^ 6 + b * Y when the color measurement value is C, the luminance is Y, the coefficient of each term is a, b, c,. ^ 5 + c * Y ^ 4 + d * Y ^ 3 + e * Y ^ 2 + f * Y + k. The order is not limited to 6, and may be less than that or more.

In addition, when one variable is made up of color values composed of a plurality of variables such as RGB values such as luminance values, in the case of a fruit of a plant such as a fruit, the occurrence time, etc., and the harvest time, ripe time, etc. It is also possible to measure color values such as RGB at one time, set the color index value as described above, and create a straight line expression passing through the two points at the two times described above as the color conversion expression. Note that when there are multiple independent variables, there are multiple straight lines for each independent variable, so multiple points are set on each of these straight lines, and the color index value and color value are displayed for each independent variable. These points may be set, and these may be subjected to multiple regression analysis to obtain the above-described color conversion formula represented by C = r * R + g * G + r * R + k.
Further, in this case, the color values such as RGB are measured at a time between the above-mentioned fruit generation time and the harvest or ripe time, and an intermediate time between the above-mentioned fruit generation time and the ripe time And a linear color conversion formula from the generation time to the intermediate time and a straight color conversion equation from the intermediate time to the complete maturity time may be set. At this time, two color conversion formulas may be set by arbitrarily changing the color index value in the intermediate period.For example, the slope of the color conversion formula is increased in the first half of the period during which the fruit grows or in the second half. You may decide arbitrarily whether to enlarge.
Further, the approximate curve is not limited to a polynomial having a second or higher order (polynomial regression analysis), and a logarithmic approximate curve (logarithmic regression analysis), an exponential approximate curve (exponential regression analysis), or the like may be used.

  If the crops are fruits, etc., the harvest time can be specified, and the color index value indicating the growth status can be used as a common recognition item. It may be. For example, if it is standardized and the color index value at the time of one month from the occurrence of fruit is 4 to 5, it can be used as a proper growth state.

A color conversion formula in each expression method is a digital color scale, and a color measurement value (color index value) as a digital color scale value is calculated from color values such as RGB extracted from a photographed image. Therefore, it is not necessary to compare the color scale, which is a color sample, with the color of the plant and read the color scale value, and the color as the digital scale value is obtained by obtaining the color value of the image by photographing with the digital cameras 1a, 1b. An index value (color measurement value) is calculated.
That is, as shown in FIG. 7, a color index value (color measurement value) as a digital scale value by, for example, a color conversion data table or a color conversion equation that becomes a digital color scale from the color value of the photographed image 31 (measurement image). Can be calculated.

  The digital color scale setting method is determined by the number of color samples, as shown in the flowchart of FIG. First, a color scale stage is determined (step S1). That is, the range of the maximum value from the minimum value of the color index value is determined. As described above, the color index value may be finally standardized and can be arbitrarily determined in the digital color scale, but the color index value as a stage is standardized by the color scale composed of the conventional color samples. In this case, the color scale stage may be used as it is. Next, color values represented by RGB or the like with respect to the minimum value and the maximum value at both ends of the color scale are determined. If there is a color scale as a color sample, the color scale is photographed and the color is extracted from the photographed image to determine the colors at both ends of the color scale. When there is no conventional color scale, the time when they occur in the case of fruits and leaves, or the time after a predetermined period from that time, is the minimum color index value (digital color scale value), and the harvest time or ripe time Are set as the maximum values, respectively (step S2).

  Next, it is determined whether the color sample (color sample) for creating the digital color scale is equal to or greater than the number of stages of the digital color scale. Then, a color value such as RGB as a color sample is associated with a color index value as a stage of the digital color scale to obtain a digital color scale (step S4). That is, it is possible to create a data table for color conversion composed of each color index value and each color value from the conventional color scale. Specifically, a color conversion formula is calculated based on the correlation between the color index value and the color value by the above-described multiple regression analysis or other regression analysis. When there is a color scale as a conventional color sample, a color conversion formula is set by this method. Further, a more detailed color conversion data table can be provided from the color conversion formula. FIG. 9 shows an RGB value obtained from an image obtained by photographing a color corresponding to each color index value of the color scale as the existing color sample shown on the line graph, and the horizontal axis represents the color index value of the existing color scale (color It is a line graph in which the vertical axis is the value of each color of RGB extracted from the photographed image (the luminance value of each color) with scale No. 1 to 7). In FIG. 9, the existing color scale provided with a color sample for each color index value is digitized, and the number of color index values is equal to the number of color values. From the data shown in this line graph, multiple regression analysis with multiple independent variables, single regression analysis using only G values of RGB values, or obtaining luminance values from RGB values and using them. By doing so, a color conversion formula can be obtained. No. of the above expression method. No. 1, no. 3, no. 4, no. 5 can be applied.

If the color sample has only values at both ends of the above-described color scale (step S5), the straight line connecting the two points is used as a color conversion formula, and each color index value is calculated from this color conversion formula as necessary. A color conversion data table is created by calculating the color values of (1). This is a method that is used to obtain color values by photographing the leaves and fruits of the actual plant that does not have a color scale consisting mainly of existing color samples. In each of the above and before that time (for example, the generation time of leaves and fruits), the leaves and fruits of the plant are photographed a plurality of times to obtain a representative value such as an average value, and two color values are obtained. The color index value can be arbitrarily set, and an early time point of two points is set to 0 or 1 etc., and a late time point is set to 10 etc., and the color value of these two points and the color index value are linear colors. A conversion formula is obtained. Although not applicable to the above-described expression method, it is the simplest method when there is no existing color scale, and is a useful method when introducing a digital color scale. FIG. 10 shows the above-mentioned minimum and maximum two points as color index values on the horizontal axis and RGB values on the vertical axis, which are connected by straight lines, but it is not necessary to use three independent variables. A straight line expression using any one variable of RGB and one variable such as luminance obtained from the RGB value can be used as the color conversion expression.
Even with such a linear color conversion formula, when the color index value (color measurement value) is obtained from the actually measured plant color value, the growth state of the crop can be assigned to each color index value. It is possible to use it sufficiently. However, when the relationship between the color value and the color index value in the period from the occurrence of crop leaves and fruits to crop harvest and fruit ripeness is a straight line, for example, when the color index value is 1-10 In the period from the beginning to 8/10, the color index value changes only from 1 to 2, but the color index value may change from 3 to 10 in the remaining 2/10 period. There is.

  Therefore, instead of the color conversion equation of one straight line connecting the above two points, the number of color samples is smaller than the number of stages of the digital color scale, but the color value ( In addition to the color sample), when obtaining a color conversion formula from three or more points by obtaining a color value in a color index value between these two color index values (step S7), for example, logarithmic approximation Thus, a color conversion formula that is a formula of a curve passing through the three points is obtained, and a data table for conversion from color values such as RGB into color index values is created as necessary (step S8). In FIG. 11, the vertical axis represents RGB values, the horizontal axis represents color index values, two points at both ends of the digital color scale described above, and points between them are plotted and approximated by a logarithmic curve. In this case as well, the color conversion formula may be calculated using one of the RGB values or the luminance value.

  Instead of approximating three or more points with a logarithmic curve, each point may be connected by a straight line in the order of the color index value, and a color conversion formula indicating each straight line may be used with the color index value of each point as a boundary. (Step S9). In FIG. 12, the vertical axis represents RGB values, the horizontal axis represents color index values, two points at both ends of the digital color scale described above, and the points between them are plotted. By subtracting the straight line connecting the point of the color and the straight line connecting the point with the middle color index value and the maximum point, the color conversion formula showing these two straight lines is divided by the color index value of the middle point to obtain the color value Used to calculate At this time, since the color value corresponding to the color index value at the midpoint is known, it is possible to determine which color conversion formula to use from the color value.

  Further, when the color index value is arbitrarily set, 0 or 1 is set as the minimum value for each of the minimum and maximum color index values, and the maximum value is a color index whose natural value is the minimum value. It is obtained by setting the number of values and adding this number −1 to the minimum value. For example, if the minimum value is 1, and the number of color index values that are natural numbers, that is, the number of color index value stages is 10, the minimum value is 1 and the maximum value is 1+ (10-1), which is 10. The intermediate point at this time may be set to 5, but the color index value corresponding to the color value measured as the intermediate point is not necessarily set to 5, and may be set arbitrarily. That is, the color index value at the midpoint can be arbitrarily set as long as it is larger than the minimum value of the color index value and smaller than the maximum value, and may be set so as to be easily used by farmers. For example, if the crop is a fruit and the primary purpose of using the color index value is to determine the harvest time, the harvest time will be between the harvest time or the ripe time slightly past the harvest time. In order to be able to assign many color index values, an intermediate point is assigned so that a large number of color index values are assigned to a range close to the maximum value at the harvest or ripe time, and a smaller color index value is assigned before that. The color index value may be arranged on the side closer to the maximum value than the median value between the minimum value and the maximum value of the color index values. Moreover, you may arrange | position conversely.

  The color scale DB 26 of the data management server 20 stores, for example, the above-described color conversion formula and color conversion data table as digital color scales of various agricultural products in each region, and the smartphone 2 on which the dedicated application A is installed. You can download it and use it. For example, when the dedicated application A is activated and a crop is selected, the above-described color conversion formula or color conversion data table is selected as the digital color scale data of the crop that is selected from the location information of the smartphone 2 and input. Downloaded. When installing a dedicated application, digital color scale data of various local crops based on the location information may be downloaded and installed in a batch.

In the application storage unit 27, the dedicated application A is registered so as to be downloadable, for example. The dedicated application A is downloaded in various application stores, and the application storage unit 27 stores links to the application store. Information may be registered.
The control unit 28 is constituted by an arithmetic processing device that controls the data management server 20 and can execute registration of data in each database, data search, and the like. For example, the control unit 28 is accessed from a terminal connected to the data management server 20, and the personal computer 10 is provided as a terminal. The personal computer 10 is a terminal operated by an organization such as an agricultural cooperative or an agricultural testing ground, and registers data in the growth target DB 23, the color scale DB 26, and the like. That is, for example, the above-mentioned institution creates, for example, a color conversion formula that becomes a digital color scale and a data table for color conversion, and creates growth target information that associates the growth status and color index values along a time series, These data are registered in each database. The above-described organization may operate the dedicated application A and the data management server 20, or may be operated by an organization such as another company. When the data management server 20 is operated by other than the above-mentioned organization, it is preferable to provide a terminal for performing management operation of the data management server 20 in addition to the personal computer 10.

An example of a method for creating a color conversion formula using the above-described existing color scale (color chart) will be described below with reference to FIG. As shown in FIG. The image of the color sample is taken with a digital camera to obtain image data. A representative value such as the average of the RGB color values of each pixel within a predetermined range of the image data is acquired. In the existing color scale shown in FIG. 13, eight-stage chart Nos. 1, 2, 3, 4a, 4b, 5a, 5b, 6 Different color samples are assigned to each. As a result, each chart No. A data table showing the RGB values for each is obtained. Based on this, a color conversion equation can be obtained by regression analysis. The line graph in FIG. The luminance value of each color of RGB for each line is shown by a line graph, and the straight line drawn for each line is the R color, G color, and B color value (luminance value) obtained by single regression analysis. And Chart No. This is a color conversion formula based on the correlation with (color scale No.). The color scale No. Are handled as serial numbers 1 to 8 that do not include alphabets such as a and b. In the line graph of FIG. 13, the R (red) value is represented by a square, the G (green) value is represented by a triangle, and the B (blue) value is represented by X. For each color of RGB, a correlation coefficient R ² and a regression line expression by single regression analysis are shown. If the value of the correlation coefficient is high, the color index value may be obtained from the value of one color of RGB.

  FIG. 14 shows correlation coefficients and regression lines obtained based on multiple regression analysis using two or three of the RGB values shown in FIG. Moreover, the correlation coefficient and regression line which are obtained based on the single regression analysis using the brightness | luminance (Y) value calculated | required from each value of RGB are shown. In this example, the correlation coefficient is the highest when all values of RGB are used, and the color index value C is calculated from the RGB values acquired from the photographed image by the above-described formula C = r * R + g * G + b * B + k. It will be required.

  Next, referring to FIG. 15, there is no existing color scale, and a digital color scale is created by obtaining a color value from image data obtained by photographing parts such as fruits (fruits) and leaves of an actual crop. . In this case, two color values are determined as described above. For example, when the target is a skin, the skin of the time when the fruit is generated and the time when the fruit is fully ripened is photographed to obtain a color value. These two color index values are set, for example, with the minimum occurrence time and the full maturity time as the maximum value, and the color value at the maximum color index value is larger than the color value at the minimum color index value. It is preferable. The color index value can be arbitrarily set and may be determined in consideration of the necessary number of steps. Further, the time corresponding to the minimum value and the maximum value of the color index value is not limited to the above-mentioned time, and may be the time when the fruit has a predetermined size or weight, for example. In the case of an annual plant, it may be the time when a predetermined period has elapsed since the seed or seedling was planted. These two points are determined by the demands of farmers and the advice of researchers.

  As described above, the color index values at two points at both ends of the digital color scale and the actual color values corresponding to the two color index values are determined, and the color index value and the color value at the point in between are determined. It is preferable that the color between the points is a color that can be used as a judgment criterion based on the demands of farmers, the advice of researchers, and the like. For example, when fruits are harvested between the time of fruit generation and the time of ripeness, any work such as the color value of the harvest time or the color value of the bagging time when bagging is performed It is preferable to set the color serving as a determination criterion when performing the process to the color value of the intermediate point.

The color index value of the point between the two points is set to the center value between the minimum value and the maximum value. As described above, the color index value of the point between the two points is small or large. It may be arbitrarily shifted.
In the graph of FIG. 15, three square points are R, three triangular points are G, and three X points are B. Two points on a straight line connecting these points between the square, triangle, and X points are set and indicated by circles. Using these points, a multiple regression analysis may be performed to obtain the above formula C = r * R + g * G + b * B + k, or the number of independent variables may be reduced to two or one. . Further, a color conversion equation may be obtained by a similar method from the minimum value and the maximum value without an intermediate point and the color value.

The color conversion formula is set by the data management server 20, for example. That is, for example, the color value obtained from the image of each sample of the existing color scale photographed using the digital cameras 1a and 1b is sent to the data management server 20 and is a numerical value assigned to the image of each sample. A certain color index value is sent from the smartphone 2 to the data management server 20, and the control unit 28 (color conversion formula setting unit) performs color conversion based on the color value obtained from the photographed image and the sent color index value. An expression is set (created) and registered in the color scale DB 26. The color value of each sample of the color scale acquired by the control unit 28 for setting the color conversion formula is not acquired from the image of each sample photographed by the digital cameras 1a and 1b. Even if a color value is directly input from the smartphone 2 or the personal computer 10 (input by a human hand or transmission of a color value acquired by the smart phone 2 or the personal computer 10 from the Internet) and sent to the data management server 20 Good. In addition, as described above, a color conversion equation is set using color values obtained from images obtained by photographing parts such as fruits (fruits) and leaves of actual crops photographed using the digital cameras 1a and 1b. It is good as well.
The creation of the color conversion formula may be performed by the personal computer 10 or the smartphone 2 as a part of the data management server 20, for example.

  In addition, the color conversion formula and the data table for color conversion may be input directly from the personal computer 10 by a person of an organization such as an agricultural cooperative or an agricultural testing ground. In this case, the input color conversion formula is sent to the data management server 20, and the control unit 28 (color conversion formula setting unit) associates the color conversion formula with a specific crop or variety and registers it in the color scale DB 26. Thus, the color conversion formula is set.

  The color conversion formula registered in the color scale DB 26 can be downloaded to the smartphone 2. The downloaded color conversion formula is stored in the color conversion formula storage unit of the smartphone 2. Further, the smartphone 2 includes a color index value calculation unit that calculates a color index value by substituting the measured color value into a color conversion formula stored in the color conversion formula storage unit. The smartphone 2 then substitutes the color values of the images taken by the digital cameras 1a and 1b into the color conversion formula to calculate the color index value, and displays the color index value on the screen.

Next, a color index value calculation method in the color index value calculation system of this embodiment will be described.
First, the data management server 20 sets a color conversion formula (digital color scale) by the above-described method (see FIG. 8), and registers the color conversion formula in the color scale DB 26 (step 1). Further, the data management server 20 registers the growth information as information relating to the growth of the crop and the color index value in association with the growth target DB 23 (step 2).
Next, in the smartphone 2, the color conversion formula set by the data management server 20 and registered in the color scale DB 26 is acquired and stored in the color conversion formula storage unit (step 3).
Thus, the color index value can be calculated.

  Next, in the digital cameras 1a and 1b, the color value of a predetermined part of the crop is measured (step 4). Specifically, the color value is acquired by photographing a predetermined part of the crop. Next, in the smartphone 2, the color value measured by the digital cameras 1a and 1b is substituted into the color conversion formula stored in the color conversion formula storage unit, and the color index value is calculated (step 5).

  Further, the smartphone 2 transmits the calculated color index value to the data management server 20 (step 6). Next, the data management server 20 that has received the color index value acquires the growth information associated with the transmitted color index value from the growth target DB 23 and transmits it to the smartphone 2 (step 7).

  The smartphone 2 displays the calculated color index value and the growth information sent from the data management server 20 on the screen of the smartphone 2 (step 8). Instead of displaying the calculated color index value and the growth information on the screen, for example, it may be output as text data so that it can be confirmed later.

  According to such a method, it is possible to calculate a color index value that is an index of the growth state, and thereby it is possible to objectively determine the growth state.

Embodiment 2. FIG.
Hereinafter, the digital cameras 1a and 1b are referred to as measurement terminals 1a and 1b. In addition, when describing with the measurement terminals 1a and 1b, it shall point out at least one of the measurement terminal 1a or the measurement terminal 1b. The smartphone 2 is referred to as a mobile terminal 2.
In the second embodiment, a color index value acquisition system including the measurement terminals 1a and 1b, the portable terminal 2, and the data management server 20 will be described. The measurement terminals 1a and 1b and the portable terminal 2 are terminals owned by the measurer. In the color index value acquisition system according to the second embodiment, the data management server 20 is not an essential configuration. Hereinafter, the description overlapping with the content described in Embodiment 1 is omitted.
FIG. 16 is a block diagram illustrating a configuration of the mobile terminal 2 according to the second embodiment. The portable terminal 2 includes a color index value control device 50. The color index value control device 50 may be provided in advance in the mobile terminal 2 or may be acquired from the data management server 20. Further, the color index value control device 50 may be configured on the data management server 20.
Hereinafter, a case where the color index value control device 50 is configured in the mobile terminal 2 will be described.
As shown in FIG. 16, the color index value control device 50 includes a color index value calculation unit 51, an output control unit 52, an image determination unit 53, a cancellation determination unit 54, a registration control unit 55, a captured image acquisition unit 56, and information acquisition. Part 57 and the like. The function of each part is realized by a processing circuit. The processing circuit may be dedicated hardware such as a processor or a CPU that reads and executes a program stored in a memory. The configuration of each unit will be described with reference to the flowchart shown in FIG.

FIG. 17 is a flowchart for explaining the operation of the color index value control apparatus 50.
When images of fruits, leaves, and the like of crops that are measurement objects are captured using the measurement terminals 1a and 1b, the captured image acquisition unit 56 acquires captured images (step ST1). Next, the image determination unit 53 determines whether there is an abnormality in the captured image acquired from the captured image acquisition unit 56 (step ST2). The case where there is an abnormality is, for example, a case where the captured image is burned.
In step ST2, when the image determination unit 53 determines that the captured image is abnormal (step ST2: YES), the image determination unit 53 outputs imaging error information to the output control unit 52 (step ST3).
When the output control unit 52 acquires the imaging error information from the image determination unit 53, the output control unit 52 displays an imaging error on the display unit 41 of the mobile terminal 2, and also generates a sound (error sound) indicating an imaging error. Then, the data is output via the audio output unit 42 of the mobile terminal 2 (step ST4). The display unit 41 is, for example, a liquid crystal display. The audio output unit 42 is, for example, a speaker. When the process of step ST4 ends, the process returns to step ST1 again.

On the other hand, when the image determination unit 53 determines in step ST2 that there is no abnormality in the captured image (step ST2: NO), the image determination unit 53 outputs the imaging success information to the color index value calculation unit 51 (step ST5). ). When the imaging success information is acquired from the image determination unit 53, the color index value calculation unit 51 calculates a color index value based on the captured image acquired from the captured image acquisition unit 56, and outputs the calculated color index value to the output control unit 52. (Step ST6).
When the output control unit 52 acquires the color index value from the color index value calculation unit 51, the output control unit 52 displays the color index value on the display unit 41, and also indicates a sound (measurement success sound) and a color index value indicating that imaging is successful. Is read out via the audio output unit 42 (step ST7). In step ST <b> 7, the output control unit 52 may display the captured image acquired from the captured image acquisition unit 56 on the display unit 41. Thus, since the color index value is read out in step ST7, the measurer can grasp the color index value without visually recognizing the display unit 41 of the mobile terminal 2. Thereby, work can be made efficient. The error sound and the measurement success sound can be selected from a plurality of sounds such as a single sound and a melody sound, and the measurer can select a sound according to the measurement environment. In addition, when working in an environment with a lot of noise or the like, a headphone is connected to the portable terminal 2, and the measurer can listen to the sound through the headphones. Thereby, missed voice can be prevented. In addition, using a wireless communication function such as Bluetooth (registered trademark) of the mobile terminal 2, sound may be output from a speaker separate from the mobile terminal 2. In this case, a plurality of workers at positions away from the measurer can simultaneously listen to the sound.

Next, the cancel determination unit 54 is a signal (cancellation signal) indicating that the measurement results are not registered from the measurement terminals 1a and 1b within a predetermined time after the color index value calculation unit 51 calculates the color index value. ) Is acquired (step ST8). The predetermined time is, for example, 10 seconds. The measurement terminals 1a and 1b are provided with a cancel operation input unit (cancel button), and a cancel signal is transmitted to the portable terminal 2 when the cancel operation input unit is operated. However, the cancel operation input unit is not limited to the cancel button, and may be any unit that can input that registration is not executed. For example, there is voice input by utterance.
The measurer listens to the color index value read out from the portable terminal 2 and, for example, if the difference between the current measurement result and the previous measurement result is large, the current measurement result and the value predicted in advance are When there is a divergence, the cancel operation input unit is operated when the measurement position of the measurement object is wrong. Therefore, the measurer can redo the measurement only by operating the measurement terminals 1a and 1b without visually recognizing or operating the portable terminal 2. Thereby, work can be made efficient.

  In step ST8, the cancel determination unit 54 determines that the cancel signal has not been acquired from the measurement terminals 1a and 1b within a predetermined time after the color index value is calculated by the color index value calculation unit 51 (step ST8). : NO), the cancellation determination unit 54 outputs a signal (cancellation non-execution signal) indicating that the cancellation is not executed to the registration control unit 55 (step ST9). When the registration control unit 55 acquires the cancel non-execution signal from the cancel determination unit 54, the registration control unit 55 determines to register the color index value calculated in the current measurement, and records it in the color index value storage unit 43 of the mobile terminal 2 ( Step ST10). The color index value storage unit 43 is, for example, a nonvolatile or volatile semiconductor memory. In step ST10, the registration control unit 55 may record the captured image together with the color index value. Further, the color index value storage unit 43 may transmit the color index value to the data management server 20. In that case, the color index value is recorded in the growth target DB 23. When the process of step ST10 ends, the process returns to step ST1 again.

  On the other hand, when the cancel determination unit 54 determines in step ST8 that the cancel signal has been acquired within a predetermined time after the color index value calculation unit 51 calculates the color index value (step ST8: YES), the cancel determination unit 54 cancels the cancellation. The determination unit 54 outputs a signal (cancellation execution signal) indicating that cancellation is executed to the registration control unit 55 (step ST11). When the registration control unit 55 acquires a cancel signal from the cancel determination unit 54, the registration control unit 55 determines to cancel the registration of the color index value calculated in the current measurement, and does not register the color index value in the color index value storage unit 43. (Step ST12). In step ST10, if the captured image is also set to be registered in the color index value storage unit 43, the registration control unit 55 also deletes the captured image. When the process of step ST12 ends, the process returns to step ST1 again.

Next, display information generation processing by the output control unit 52 will be described.
The output control unit 52 controls information displayed on the display unit 41 of the mobile terminal 2. FIG. 18 is a flowchart for explaining display information generation processing in the output control unit 52.
The output control unit 52 outputs information indicating that the color index value is acquired from the color index value calculation unit 51 (color index value acquisition information) to the information acquisition unit 57 (step ST21).
Next, when acquiring the color index value acquisition information from the output control unit 52, the information acquisition unit 57 acquires additional information (details will be described later) to be displayed on the display unit 41 together with the color index value, and the output control unit 52 (Step ST22). The additional information can be set in advance by the measurer via the portable terminal 2 or the like. For example, the information acquisition unit 57 acquires additional information from the data management server 20. Further, the information acquisition unit 57 may acquire information acquired by the mobile terminal 2.
Next, the output control unit 52 generates display information to be displayed on the display unit 41 based on the color index value acquired from the color index value calculation unit 51 and the additional information acquired from the information acquisition unit 57. 41 (step ST23).

FIG. 19 is a diagram illustrating an example of display information generated by the output control unit 52.
FIG. 19 shows a case where the information acquisition unit 57 acquires a measurement date, a field name, a section name, a measurement count, a set count, and color scale information as additional information. The measurement date, field name, and section name may be directly input by the measurer. The set number of times is a predetermined number of times for each measurement point on the farmland or the like. The measurer performs measurement (photographing) at the measurement point until the set number of times is reached. The number of measurements may be calculated by the color index value calculation unit 51.

  In FIG. 19, the output control unit 52 displays the average value of the color index value measurement results (color index values) calculated by the color index value calculation unit 51 and the captured image acquired from the captured image acquisition unit 56. It shows the case of information.

  The color scale information is information in which color sample images indicating colors of crops such as fruits and leaves are arranged in time series for each stage of growth of fruits and crops. In addition, each color sample image is associated with a color index value, and the output control unit 52 displays the color index value at each stage so as to overlap the color sample image.

  Further, the output control unit 52 displays plot information in a form corresponding to the scale below the scale of the color index value of the color scale information. The plot information is information representing the color index value acquired from the color index value calculation unit 51 with a symbol. The output control unit 52 displays the latest measurement result (the 12th time in FIG. 19) with a triangular symbol. The previous measurement results are displayed with diamond symbols. The measurement result in the first half of the measurement can be confirmed by scrolling the right bar on the display unit 41. Further, the output control unit 52 displays a circle symbol, which is a symbol indicating an average value from the first measurement result to the most recent measurement result, overlaid on the color sample image of the color chart information. The measurer can grasp the transition of the measurement result by looking at the display unit 41 and intuitively understand how much the measurement result is deviated from the average value or other measurement results. As a result, it is possible to examine measures such as whether or not to perform measurement again.

  Further, as described above, the output control unit 52 outputs the voice that reads out the latest measurement result via the voice output unit 42. For this reason, the measurer can grasp the measurement result both visually and auditorily. Thereby, oversight and missed hearing can be prevented, and work efficiency can be improved. Further, for example, when the measurer is performing measurement using the measurement terminals 1a and 1b with the portable terminal 2 placed in a pocket of work clothes, the measurer visually recognizes the display unit 41 of the portable terminal 2. The measurement results can be grasped by hearing. In addition, since sound is output from the mobile terminal 2 instead of the measurement terminals 1a and 1b, for example, when the operator extends the hand with the measurement terminals 1a and 1b, the position of the ear of the measurer is further increased. Sound is output from the mobile terminal 2 near the. For this reason, it is possible to prevent the voice from being missed and to improve the work efficiency. Further, when the output control unit 52 acquires information indicating that the number of measurements has reached the set number of times (measurement completion information) from, for example, the color index value calculation unit 51, the output control unit 52 displays information indicating that the measurement is completed. At the same time, output audio. For this reason, the measurer can grasp both the visual and auditory senses that the measurement has been completed.

FIG. 20 is a diagram illustrating another example of display information generated by the output control unit 52.
FIG. 20 illustrates a case where the information acquisition unit 57 acquires past information as additional information.
The past information is information indicating an average value of measurement results of past dates at the same measurement point. The output control unit 52 plots and displays past information, for example, below the display unit 41. Therefore, the measurer can intuitively grasp how much the measurement result of today is deviated from the measurement result of the past date. Thereby, correspondence, such as whether to spread fertilizer, can be examined.

FIG. 21 is a diagram illustrating another example of display information generated by the output control unit 52.
FIG. 21 shows a case where the output control unit 52 displays abnormal value information on the display unit 41. The abnormal value information is information indicating that the measurement result is an abnormal value. The output control unit 52 displays the measurement result symbol corresponding to the abnormal value in a state of being painted red. However, any method other than painting may be used as long as it is an aspect that shows an abnormal value. The color index value calculation unit 51 determines whether or not the measurement result is an abnormal value. For example, the color index value calculation unit 51 determines that the measurement result is abnormal when the difference between the measurement result and the average value is 1.5 or more, or when the measurement result is not within the range of 2σ of the standard deviation. It is determined that When the color index value calculation unit 51 determines that the measurement result is abnormal, the color index value calculation unit 51 outputs information indicating an abnormal value together with the measurement result to the output control unit 52. When the output control unit 52 acquires the information together with the measurement result, the output control unit 52 displays abnormal value information on the display unit 41. At this time, the output control unit 52 may output a sound indicating that the measurement result is an abnormal value.

FIG. 22 is a diagram illustrating another example of display information generated by the output control unit 52.
FIG. 22 shows a case where the information acquisition unit 57 acquires appropriate harvest time information and remaining days information as additional information. The appropriate harvest time information is information indicating the date of the appropriate harvest time for crops and the like. The remaining days information is information indicating the remaining days until the harvest date. The remaining number of days is stored in association with the color index value. The appropriate harvest time information and the remaining number of days information are managed by agricultural cooperatives, agricultural test stations, government offices, or research institutions. The output control unit 52 displays the remaining days information in a frame shape, for example, superimposed on the color chart information and the plot information. In FIG. 22, when the color index value is 4.1 to 5.5, it indicates that the remaining number of days until the appropriate harvest time is 10 to 15 days. For this reason, the measurer can intuitively know how many days are left until the optimum harvest time. As a result, it is possible to consider measures such as determining the harvest date, and the work can be made more efficient.

FIG. 23 is a diagram illustrating another example of display information generated by the output control unit 52.
FIG. 23 shows a case where the output control unit 52 further displays other section information on the display unit 41 in addition to the example of FIG. The other section information is information indicating an average value of measurement results in other sections on the same day. The output control unit 52 plots and displays the other section information on the lower side of the display unit 41, for example. For this reason, the measurer can intuitively grasp the deviation of the measured value between the currently measuring section and the other sections. Thereby, for example, it is possible to adjust the schedule such as whether the section currently being measured and which other section are harvested on the same day. For example, in the case shown in FIG. 23, it can be determined that the section D currently being measured and the sections A, E, and F are harvested on the same day. Thereby, work can be made efficient.

FIG. 24 is a diagram illustrating another example of display information generated by the output control unit 52.
FIG. 24 illustrates a case where the information acquisition unit 57 acquires management range information as additional information. The management range information is information indicating the range (management range) of color index values determined by agricultural cooperatives, research institutions, and the like. The management range is defined by cultivation guidelines and the like. The output control unit 52 displays the management range information in a frame shape, for example, overlapping the plot information. Further, the color index value calculation unit 51 acquires management range information from the data management server 20, and determines whether or not the measurement result (color index value) is within the management range. When it is determined that the measurement result is not within the management range, the color index value calculation unit 51 outputs information indicating that the measurement result is out of the management range together with the measurement result to the output control unit 52. When the output control unit 52 acquires the information together with the measurement result, the output control unit 52 displays the measurement result on the display unit 41 as abnormal value information, similarly to the case shown in FIG. At this time, the output control unit 52 may output a sound indicating that the measurement result is a value outside the management range. Further, the output control unit 52 transmits the measurement result and information (flag) indicating that it is out of the management range to the data management server 20. When the data management server 20 receives the information, the data management server 20 automatically transfers the information to a terminal owned by an administrator, a contract instructor, or the like. When an administrator or the like inputs treatment (treatment information) for an abnormality such as application of fertilizer to the terminal, the treatment information is transmitted to the portable terminal 2 via the data management server 20 and stored in the data management server 20. Is done. In the above description, the administrator or the like inputs the treatment information to the terminal. However, the data management server 20 may have a learning function so that the data management server 20 automatically returns the treatment information. .

  As described above, according to the color index value acquisition system or the color index value acquisition method according to the second embodiment, the sound for reading the color index value is output from the mobile terminal 2 and the color index value control apparatus 50 When the cancel signal is acquired from the measurement terminals 1a and 1b, the color index value is deleted without being registered. For this reason, the measurer can redo the imaging only by the operation on the measurement terminal 1a, 1b side without visually recognizing or operating the portable terminal 2. Thereby, work can be made efficient.

  Further, according to the color index value control device 50 or the color index value control method according to the second embodiment, the measurer can grasp information on which stage the current growth stage of the measurement object is, and adjust the schedule. The future correspondence such as can be considered. Thereby, work can be made efficient.

Finally, the measurement terminal 1a will be described.
Fig.25 (a) is the figure which looked at the measurement terminal 1a from the front. FIG. 25B is a diagram of the measurement terminal 1a as viewed from above. FIG. 25C is a side view of the measurement terminal 1a as viewed from the left.
FIG. 26 is a view of the measuring terminal 1a as viewed from the front, and shows a state in which the head portion 62 is open. FIG. 27 is a cross-sectional view of the measurement terminal 1a. In FIG. 27, hatching indicating a cross section is omitted.
As shown in FIG. 25A, the measurement terminal 1a includes a main body portion 61, a head portion 62, and a switch portion 63. The main body 61 is provided with a power button 71 and a cancel operation input unit (cancel button) 72. Moreover, as shown in FIG. 26, the base part of the head part 62 is being fixed to the main-body part 61 so that rotation is possible. A leaf or the like to be measured can be sandwiched between the main body portion 61 and the head portion 62. A urethane rubber 64 is attached to the main body 61 side of a portion (called a measurement object clamping portion) that sandwiches the measurement object. By using the urethane rubber 64 having elasticity, it is possible to prevent the measurement object from being damaged.

As shown in FIG. 25B, the head portion 62 is provided with a switch portion 63. The switch part 63 has a base part fixed to the main body part 61 so as to be rotatable together with the head part 62, and a base part fixed to the main body part 61 so as to be movable independently of the head part 62.
As shown in FIG. 27, the switch part 63 is provided with an elastic body accommodating part 63a and a shaft pressing part 63b. The elastic body accommodating portion 63a is a portion standing in a cylindrical shape on the back side of the switch portion 63, and the first elastic body 81 is accommodated therein. The first elastic body 81 is, for example, a spring. One end side of the first elastic body 81 is accommodated in the elastic body accommodating portion 63 a, and the other end side is in contact with the flat surface portion 62 a of the head portion 62. The first elastic body 81 is biased so as to push up the switch unit 63 on the side opposite to the measurement object clamping unit side (the lower side in FIG. 27).

  The shaft pressing portion 63b is a portion erected in a columnar shape on the back side of the switch portion 63, and is formed so that a shaft 82 described later can be pressed. As shown in FIG. 27, when the switch unit 63 is not pressed, a gap is formed between the tip of the shaft pressing unit 63b and the end of the shaft 82. When the switch part 63 is pressed and the first elastic body 81 is bent by a predetermined amount, the tip of the shaft pressing part 63 b comes into contact with the end of the shaft 82.

  The shaft 82 is supported inside the head portion 62 so as to be movable in the axial direction. When one end of the shaft 82 is pressed by the shaft pressing portion 63b, the shaft 82 moves to the side opposite to the switch portion 63 side (the lower side in FIG. 27). A pin pressing portion 82a is attached to an end portion of the shaft 82 opposite to the side in contact with the shaft pressing portion 63b. The pin pressing part 82a has a pressing surface 82b for pressing a pin 83 described later. The pressing surface 82b is formed so as to be inclined toward the pin 83 side (lower side in FIG. 27), which will be described later, as it goes to the opposite side of the surface to be measured with respect to the surface perpendicular to the axial direction of the shaft 82. ing.

  The pin 83 is supported inside the main body 61 so as to be movable coaxially with the shaft 82. One end of the pin 83 is disposed so as to contact the pressing surface 82b of the pin pressing portion 82a. A second elastic body 84 is attached to the other end side of the pin 83, and the second elastic body 84 biases the pin 83 so as to push it up to the shaft 82 side (upper side in FIG. 27). . The second elastic body 84 is, for example, a spring. A switch 85 is disposed on the end side of the pin 83 opposite to the side in contact with the pressing surface 82b with a predetermined gap from the pin 83. When the pin 83 moves to the switch 85 side against the urging force of the second elastic body 84 and the end portion of the pin 83 depresses the switch 85, the switch 85 is turned on to control driving of the LED, the image sensor, and the like. The power supply of the control circuit is turned on. Thereby, the measurement object clamped by the measurement object clamping part is imaged.

  When the measurer turns the head unit 62 and the switch unit 63 to pinch the measurement target, the head unit 62 (switch unit 63) stops depending on the thickness (shape) of the measurement target (hereinafter, this state is pinched). Called state). The first elastic body 81 uses a spring having a spring constant larger than that of the second elastic body 84, and the measuring terminal 1a is in a sandwiched state and the switch 85 is turned on only when the switch portion 63 is not pushed further. It is not to become. If the configuration is such that the switch 85 is not turned on unless the head portion 62 is further rotated from the sandwiched state, there is a problem that a pressing load is applied to the measurement target and the measurement target is damaged. In the measurement terminal 1a, the switch unit 63 is provided so as to be movable independently of the head unit 62, and only the switch unit 63 can be pushed in, so that measurement can be performed without damaging the measurement object. Can do.

1a, 1b Measurement terminal 2 Mobile terminal 50 Color index value control device 51 Color index value calculation unit 52 Output control unit 54 Cancel determination unit 55 Registration control unit

Claims (2)

A color index value acquisition system comprising: a measurement terminal that images a measurement object; and a color index value control device that is communicably connected to the measurement terminal,
The color index value control device includes:
A color index value calculation unit that calculates a color index value based on a captured image acquired from the measurement terminal;
An output control unit for outputting a voice from a mobile terminal possessed by the measurer with the color index value;
A cancel determination unit that determines whether or not a cancel signal indicating that registration of a measurement result is not performed is acquired from the measurement terminal;
A registration control unit that controls registration of the color index value;
The registration control unit deletes the color index value without registering the color index value when the cancellation determination unit determines that the cancellation signal has been acquired. A color index value acquisition method using a measurement terminal that captures an image of a measurement object and a color index value control device that is communicably connected to the measurement terminal,
A calculation step in which a color index value calculation unit calculates a color index value based on a captured image acquired from the measurement terminal;
An output control step, wherein the output control step outputs sound from a portable terminal possessed by the measurer with the color index value;
A cancellation determination step for determining whether or not the cancellation determination unit has acquired a cancellation signal indicating that registration of measurement results is not performed from the measurement terminal;
A registration control unit comprising a registration control step for controlling registration of the color index value;
In the registration control step, when it is determined that the cancel signal is acquired in the cancel determination step, the color index value is deleted without registering the color index value.