KR101661708B1 - System for observing seasons based on images and the method thereof - Google Patents

Abstract

The present invention relates to a system and method for evaluating a color of autumn leaves through observation of a map of autumn leaves. The autumn leaves are observed for each mountain in autumn, the degree of autumn leaves is evaluated by calculating a coloring ratio, It is possible to improve the convenience of travelers by predicting the progress of the colored leaves to be proceeded, to help attract tourists to sightseeing spots, and also to distribute travelers by providing information of the autumn leaves, thereby reducing traffic congestion.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image-based seasonal observation system,

The present invention relates to an image-based seasonal observation system and method, and more particularly, to a method and system for observing an image based on seasonal observation of autumn leaves, in which autumn leaves are observed for each mountain in autumn, autumn leaves are observed, This system is designed to improve the convenience of travelers by predicting the progress of colored leaves in the future, to help attract tourists to tourist destinations, and to provide information on maple leaves to reduce traffic congestion by distributing travelers. And to propose the method.

Currently, weather-related organizations are observing seasonal changes by animal observations, observations of animal emergence, degree of flowering of plants, and progress of colored leaves of Mt. Myungsan.

Recently, the demand for detailed information about the maple leaves is increasing due to the increase of leisure time of the people, and there is a limitation in providing detailed information such as the beginning and peak of the colored leaves of Mt.

As a result of analyzing the public interest in autumn, the autumn leaves of the autumn foliage have shown the highest degree of interest. It is also remarkable that the interest of the autumn leaves of autumn is mentioned among people through blogs rather than news and Twitter. Among the many places related to autumn mentioned in these blogs, the mountain appeared the most.

As a result of analyzing the major issues of autumn leaves, major issues related to autumn leaves are emerging as weather forecasts, parking lots, safety accidents, autumn foliage, theme parks, autumn leaves, autumn festivals, and field trips. In particular, many people showed that they are watching the weather forecast together ahead of the autumn leaves. It can be seen that the related safety accidents along with the autumn hiking and outing are also big issues. In addition, since many congestion occurs on the expressway during the autumn foliage season, it is necessary to provide information on the maple leaves in various places to disperse the travelers, to reduce regional variation, and to provide information on new tourist attractions.

Recently, there is a growing need to provide more accurate and more detailed status information (eg, maple leaves) to disperse tourists locally when meeting the right to know people and going out for seasons. In addition, local governments where tourist attractions are located are able to create new added value by promoting information on local tourist attractions in real time, and this need is increasing.

Therefore, the present invention improves the convenience of travelers by observing and predicting the progress of the colored leaves in each mountain in the fall, helps attract tourists to tourist destinations, and distributes travelers by distributing map information. And a method of evaluating the color of the leaves through the observation of the map based on the image.

Next, a brief description will be given of the prior arts that exist in the technical field of the present invention, and technical matters which the present invention intends to differentiate from the prior arts will be described.

Korean Unexamined Patent Publication No. 2005-0039441 (Apr. 29, 2005) discloses a method for providing and acquiring comprehensive support for travel by a two-way communication network, a communication system and a program thereof, and a display screen When the user designates a desired earth, the photograph screen is transmitted. The photograph of the season landscape can be displayed on the screen by selecting the landscape of the four seasons or the current season landscape. In addition, if the current landscape photographed by the photographer on the mobile phone by the travel consumer is imported into the database device as tourist facility information by posting and released, the seasonal scenery can be viewed in a more real- Is disclosed.

However, according to the prior art, only the seasonal scenery can be seen by showing the image information previously prepared by the traveler or the system to the traveler, and it is possible to observe and forecast the degree of the autumn foliage in each mountain in autumn, It does not provide a technical structure that improves convenience and helps tourists to attract tourists.

Accordingly, the present invention provides an image-based seasonal observation system and a method thereof, thereby providing an observation and a forecast of autumnal map information in autumn, thereby improving the convenience of travelers, helping attract tourists to sightseeing spots, We propose a system for evaluating the condition of the leaves and a method for reducing traffic congestion.

The present invention has been made in order to solve the above problems, and it is an object of the present invention to extract color foliage region by color model based on a photographed image of a specific mountain, The present invention also provides an image-based seasonal observation system and a method thereof, which are provided by performing an evaluation on a map of autumn leaves.

The present invention also provides an image-based seasonal observation system and method for predicting the progress of a colored foliage, which further reflects a weather condition because the progress of the foliage is affected by a weather or an environment.

It is another object of the present invention to provide an image-based seasonal observation system and method capable of predicting how far the colored leaves will progress in the future while accumulating information on the respective proceeding speeds of individual leaves according to the kinds of trees do.

Further, the present invention provides an image-based seasonal observation system and method capable of accurately estimating the progress of current colored foliage through observation of colored foliage and predicting the progress of colored foliage based on information on the progress speed of colored foliage depending on weather or trees And to provide the above objects.

It is another object of the present invention to provide an image-based seasonal observation system and method which can provide a map of autumnal leaves, a maple ratio, a map of autumn leaves, or a combination thereof.

In addition, the present invention relates to a system and method for evaluating a color of autumn leaves through observation of a map of autumn leaves. In autumn, the degree of progress of colored leaves for each mountain is observed, Image-based seasonal observation system and method that can reduce the congestion of traffic by distributing travelers by providing map information and helping attract tourists to tourist attractions by predicting the progress of colored leaves in the future And to provide the above objects.

An image-based seasonal observation system according to an embodiment of the present invention includes an observation area extracting unit for extracting an observation area for a map from a map image; A color extracting unit for extracting a color from the extracted observation area; A mapper area calculation unit for calculating a map area based on the extracted color; And a green state determining unit for determining a green state by calculating a reddish rate from the calculated reddish area.

The image-based seasonal observation system may further include: a maple image collection unit for collecting maple images from at least one maple camera; And a storage interface unit for storing information on the map image and the map information.

Further, the observation area extracting unit is characterized by being determined as the area of a tree to which a maple leaves by excluding a part unrelated to a maple including rocks, evergreens, sky, buildings, or a combination thereof.

Also, the color extracting unit extracts a color of a maple color using at least one color model of RGB, HSV, HLS, CMYK, or CMY, and the color corresponding to the maple color includes yellow, red or brown .

Also, the map area calculation unit calculates the entire observation area and the map area, and the entire observation area includes a map area and a green area, and the map area includes a red area, a yellow area, a brown area, .

Further, in the above-described map determining unit, the mapper ratio is characterized by indicating the percentage of the map area in the entire observation area as a percentage.

In addition, the image-based seasonal observation system can predict the progress of the autumn colored leaves according to the meteorological conditions of the mountain where the autumn colored leaves are photographed, or predict the direction of the autumn colored leaves based on the information on the progress speed of the colored leaves, And a step of predicting whether or not the backward colored leaves will progress, and is characterized in that it can provide a map of autumn leaves, a maple leaf ratio, a map of autumn leaves, or a combination thereof.

In addition, the map area calculating unit may include calculating an area of a map or the like by dividing the map into ten regions based on altitude obtained by dividing the map by ten tiers from the normal of the observed region in the extracted observation area, When the leaves are observed up to the above-mentioned 10% of the altitude at the top, the first colored leaves are judged to be the first colored leaves. When the colored leaves are observed up to the 80% And the like.

According to still another aspect of the present invention, there is provided an image-based seasonal observation method comprising: an observation area extracting step of extracting an observation area of a maple from an autumn map image; A color extracting step of extracting a color in the extracted observation area; A colored area calculating step of calculating a colored area based on the extracted colors; And a mapper state determining step of determining a mapper condition by calculating a mapper ratio from the calculated mapper area.

The image-based seasonal observation method may further include: a map image collection step of collecting a map image from at least one map image taking camera; And storing information on the map image and the map data.

Further, the observation region extracting step is characterized in that it is determined as the area of the tree where the maple leaves, by excluding the part not related to the maple leaves including rocks, evergreens, skies, buildings or a combination thereof.

In addition, the color extracting step extracts the color of the colored leaves using at least one color model of RGB, HSV, HLS, CMYK, or CMY, and the color corresponding to the colored leaves includes yellow, red or brown .

Also, the calculating of the map area may include calculating a total observation area and a map area, wherein the entire observation area includes a map area and a green area, and the map area includes a red area, a yellow area, a brown area, .

Further, in the step of determining the colored state of the leaves, the colored leaves ratio is characterized by representing the percentage of the colored leaves in the entire observed area as a percentage.

In addition, the image-based seasonal observation method may further include a step of predicting whether or not the foliage of the foliage is proceeding according to the weather conditions of the mountain where the foliage image is photographed, And a step of predicting whether or not the backward colored leaves will progress, and is characterized in that it can provide a map of autumn leaves, a maple leaf ratio, a map of autumn leaves, or a combination thereof.

The present invention constructed as described above relates to a system and method for evaluating a colored state of leaves through observation of colored leaves. In autumn, the degree of progress of colored leaves for each mountain is observed, and the amount of colored leaves is calculated by evaluating the degree of colored leaves The present invention also has an effect of reducing traffic congestion by distributing travelers by providing information on maple leaves to improve the convenience of tourists by predicting the progress of the colored leaves to be carried out in the future.

1 is a service conceptual diagram illustrating a concept of providing a seasonal observation service through an image-based seasonal observation system according to an embodiment of the present invention.
FIG. 2 is a block diagram for explaining a step of observing colored leaves in an image-based seasonal observation system according to an embodiment of the present invention.
3 is an example of an image for explaining a concept of excluding an evergreen community from an observation area in an image-based seasonal observation system according to an embodiment of the present invention.
FIG. 4 is a diagram illustrating a process of extracting an area of colored leaves through color extraction in an image-based seasonal observation system according to an exemplary embodiment of the present invention.
FIG. 5 is a diagram illustrating an example of a process of calculating a map ratio in an image-based seasonal observation system according to an exemplary embodiment of the present invention.
FIG. 6 is a diagram illustrating a process of calculating a red-leaf ratio using an HLS color separation technique in an image-based seasonal observation system according to an exemplary embodiment of the present invention.
7 is a diagram illustrating a process of extracting a map area based on altitude in an image-based seasonal observation system according to an exemplary embodiment of the present invention.
FIG. 8 is a process flowchart of a seasonal observation method using an image-based seasonal observation system according to an embodiment of the present invention.

Various embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a service conceptual diagram illustrating a concept of providing a seasonal observation service through an image-based seasonal observation system according to an embodiment of the present invention.

As shown in FIG. 1, a mapper observation infrastructure is built in famous mountains in the country or in the world, and a camera 200 for photographing a mountain is installed in each map observation infra, and a camera installed in a mountain or a forest It is connected to the management office via wired / wireless Internet or optical line. The image transmitted from each camera through the system installed in the management office or the network equipment is transmitted to the season observation system 100 through the wired / wireless network. Here, a camera installed in each mountain or forest is directly connected to a wired / wireless Internet and can transmit a photographed image to the season observation system 100. The seasonal observation system can receive various images every season from the camera 200 installed in each mountain or forest.

Based on the images thus provided, the seasonal observation system 100 observes the autumnal colors and provides the results to the wired / wireless user terminal 300. In addition, the seasonal observation result can be stored in the database 400 and used as a reference data for the seasonal observation.

Since the database 400 operated for this purpose may lack space for storing the image data collected in the whole country, information for the period from the beginning to the end of the colored leaves is intensively stored, It saves the storage space of the database by storing the image only when significant change is detected in the format and storing the main information in the text as summarized text.

The wired / wireless user terminal 300 can be connected to the seasonal observation system on a web-based basis. The wired / wireless user terminal 300 can be connected to the seasonal observation system by simply providing information on the speed of the foliage, expected weather information, traffic information, And provide various information in a comprehensive manner.

For this purpose, the seasonal observation system connects with servers or databases of other institutions (eg, weather, traffic, and forest related organizations) and combines information from various agencies to provide more sophisticated travel information.

Leaves are a dictionary meaning that leaves change from green to red, yellow or brown depending on climate change. When the average temperature falls below 13 ~ 14 per day, the color of the leaves is formed on the leaves of the deciduous leaves and the sugar chains do not move to the stem, so that the green chlorophyll is destroyed and the pigments hidden by the chlorophyll appear Or that the leaf that was in the leaf while it is in the leaf is changed into the pigment which was not in the leaf until that time.

The reddish leaves are called "autumn leaves" in particular, while the red leaves appear because the anthocyanin pigment is formed in the leaves. Anthocyanins begin to be made only when the chlorophyll in the leaves is getting smaller, and also when the weather is very clear and the water is low in the air, it starts to be made when it gets cold and it is made more when it is sunny. Anthocyanins are also produced by the conversion of substances such as sugar produced by photosynthesis. Before the leaves fall in autumn, the petiole is shaken (leaves, flowers, fruit tissue or follicle layer formed when the fruit falls from the stem), and the sugar made from the leaves is transferred to another place Because it accumulates in the leaves without supporting, the sugar turns into anthocyanin, and the leaves are colored. Trees that are reddish in color include maple trees, mountain cherry trees, arrow trees, rhinos, lacquer trees, corolla trees, melancholic trees, and yinori trees.

Also, yellowing like ginkgo trees is because there are many carotenoids in the leaves. This pigment is made with chlorophyll when the leaf is made, but is only 1/8 of the chlorophyll. Therefore, when the leaves are first made, they are green by the chlorophyll, but fall into the autumn, and the chlorophyll is destroyed and the leaves become yellow or brown, which is the color of the carotenoid. The trees that are yellowed are Noshiro, Elm, Poplar, Pine, and Sycamore.

In addition, the leaves are brownish because the anthocyanin is produced in place of tannin. Tannins, like anthocyanins, are produced by chemical reactions such as sugar, but at the very last stage they go through a different pathway than anthocyanins. There are many carotenoids in the leaves, even though they are brownish leaves, and because of the combination of tannins and anthocyanins, they exhibit various color combinations. Trees that are brown with leaves include zelkova trees and conifers.

In the present invention, the kind and color of trees in a specific mountain are analyzed based on the color characteristics of the above-described colored leaves, and the color is separated from the defined map area to analyze and analyze the degree of colored leaves.

First, we will review the evaluation criteria for colored leaves. At present, the person in charge of evaluating the autumn leaves of the institution judges the color of the autumn leaves and the size of the area at the top of the mountain by subjective judgment and determines the first autumn leaves. The maple leaves are the first maple leaves when it is dyed from the top of the mountain by about 20% (20%), and the maple peak is when the dyed below the top of the mountain is about 80% (80%).

Currently, the first autumn leaves and the peak season are judged by people, and pictures are taken and posted. Therefore, it is difficult for an individual to quantitatively observe the developmental state of a plant, and there is a possibility of causing a mistake or judgment error. In addition, it requires long experience to observe the foliage, and it is difficult for the individual to take charge of the difference due to subjectivity and to take over the business.

Therefore, it is necessary to express it quantitatively instead of the subjective result of subjective judgment of the person in charge of evaluating the colored leaves. That is, in the present invention, a method of defining the map area based on the previous image data of a specific mountain, performing color separation in the defined map area, and measuring the degree of color of the map. If the measured degree of leaf color is 20% or more of the observation interval, it is judged as the first colored leaf.

The observation section is in accordance with the Meteorological Agency observation standard. For example, the observation section can be determined by dividing the mountain peak at the elevation of elevation into 10 or 20 sections. The evaluation of the maple leaves can be determined by measuring five times a day (09:00, 11:00, 13:00, 15:00, 17:00). Table 1 below lists the colors of the leaves and representative trees.

I will explain the method of evaluating the color of the leaves based on the color of the leaves, the pigment of the corresponding color, and the representative tree.

FIG. 2 is a block diagram for observing and evaluating the color of an image-based seasonal observation system according to an exemplary embodiment of the present invention.

2 (a), the image-based seasonal observation system 100 according to the present invention includes a network interface unit 110, a maple image collection unit 120, a foliage condition observation unit 130, a storage interface unit 150 and a user interface unit 140.

The network interface unit 110 serves as a path for collecting image information from a camera installed in mountains or forests all over the wired / wireless network, and is used for a database 400 connected to a network or for interaction with a user terminal 300 It acts as a channel.

The maple image collection unit 120 periodically collects images from the camera 200 and stores the collected images. That is, the image transmitted from the camera is classified by time and place, and is stored in the database through the storage interface unit 150. In addition, the collected image information is transmitted to the foliage condition observation unit to monitor the state of the foliage, And collects and provides images. In addition, when a request for a color change is requested from a color change state monitoring unit, a desired image can be received from a camera at a corresponding place in real time.

The autumnal state observing unit 130 performs a core function in the image-based seasonal observation system 100 of the present invention, which will be described in detail below.

The storage interface unit 150 stores the images collected by the map collecting unit 120 or the information observed by the mapper observing unit 130 in the database or the information about the reference images already stored in the map monitoring unit 130 And accesses and transmits the data according to the request of the user. If the database is connected to the network as required, the image or observation information can be stored in the database through the network interface unit 110, and the reference image and the desired conventional map data can be accessed.

The user interface unit 140 provides a user interface for controlling the image-based seasonal observation system 100 according to the present invention through a user terminal. The user interface is used as an input / output interface for requesting foliage observation information using a user interface screen displayed through a wired / wireless terminal or for controlling the system.

Referring to FIG. 2B, a detailed procedure is shown for the autumnal state observing unit 130. The autumnal state observing unit 130 of the present invention includes an observation area extracting unit 131, a color extracting unit 132, a colored area calculating unit 133, and a colored map determining unit 134.

Here, the observation region extracting unit 131 extracts an observation area of the maple leaves from the collected image, and extracts a region of a region (ROI, Region Of Interest) considered to be colored. In particular, the reliability is improved by removing the area of a portion where it is difficult to measure colored leaves such as rocks. By using the image processing, the part other than the area of interest is removed and excluded from the map area so that the image processing is not performed.

In addition, the observation area extracting unit 131 extracts the area to be observed once, removes the area of the evergreen community with four seasons green, and extracts the observation area using the data of the past mountains.

Utilizing past measurement data stored in the database 400, an exception processing and observation part for an area other than the maple leaves (for example, rocks and evergreen communities) is extracted.

For example, FIG. 3 is an example of an image for explaining a concept of excluding an evergreen community from an observation area in an image-based seasonal observation system according to an embodiment of the present invention.

First, if there is an evergreen in the original image, the color of the area is extracted and the color area, that is, the area that is always green or the area corresponding to the rock is excluded from the observation area. For this purpose, a mask for the target area is covered, and finally a portion corresponding to the map area is extracted.

Next, the color extraction unit 132 performs a function of extracting colors other than the colors of leaves and leaves. The color space is color separated using HSV (Hue, Saturation, Value (Brightness)) color model, HLS color model, RGB color model or a combination thereof, . In addition, color models include CMY and CMYK color models, which are well known in the art and will not be described in detail.

Here, the RGB color model is a color model made by adding and mixing the colors of Red, Green and Blue. Since a specific color is expressed by a mixture of R, G, and B, And extracts how much each is included. Using the RFG color model, it is possible to observe how the foliage of a particular tree collected by the camera is changed. That is, it is possible to extract R, G, and B color components from the color information of the image photographed by the camera in a state in which the color information of the corresponding colored leaves of the tree is known, and predict the color of the corresponding tree. It is also possible to estimate the progress of the colored leaves by calculating the area having the corresponding color.

The HLS color model is a color model made up of hues, lightness, and saturation. It analyzes the color information of a particular colored leaf as a component of color, lightness, and saturation, And the like.

FIG. 4 is a diagram illustrating a process of extracting an area of colored leaves through color extraction in an image-based seasonal observation system according to an exemplary embodiment of the present invention.

As shown in FIG. 4, an image of a foreground of a mountain is collected by a camera, an observation region is set in the image of the mountain, and regions of green, yellow, red, and brown are extracted.

Referring to the upper side of FIG. 4, a mask is covered by the rocks and the evergreen (green part) community in the observation area. I extract the parts with yellow, red and brown in the rest of the part. Thus, the area of colored leaves can be extracted. Also, referring to the lower side of FIG. 4, the middle part of the evergreen area is masked and removed. Next, yellow, red, and brown areas are extracted for the remaining area to observe the state of the colored leaves.

FIG. 5 is a diagram illustrating an example of a process of calculating a map ratio in an image-based seasonal observation system according to an exemplary embodiment of the present invention.

As shown in FIG. 5, the area of the maple leaves can be calculated based on the extracted color values. That is, the mapper ratio can be calculated by (map area) / ( observation area) * 100 = map map ratio (%). Here, the map area can be calculated as the map area = red area + yellow area + brown area, and the entire observation area can be calculated with observation area = (map area + green area).

The map area calculation unit 133 calculates an area of the area where the color is red, yellow, or brown in the observation area. In other words, the color extraction unit 132 calculates the map area based on the color extracted by the color extraction unit 132.

Next, the mapper status determination unit 134 calculates the mapper ratio from the calculated map area, and determines the mapper status. That is, in the present invention, for example, if the calculated amount of the maple leaves is 20% or more, it is evaluated as the first colored map, and when it is 80% or more, the map is evaluated as the colored map.

These ratios are an embodiment, and the ratios may be varied depending on the tree or the locality. Depending on the northern or southern part of the country, if the duration of the leaves is short or long, more than 90% of the leaves may last for a long time. If the leaf color ratio is 70% It is preferable to variably set the first colored leaves and the peaked state depending on the case.

FIG. 6 is a diagram illustrating a process of calculating a red-leaf ratio using an HLS color separation technique in an image-based seasonal observation system according to an exemplary embodiment of the present invention.

As shown in FIG. 6, the green image is extracted through the HLS color separation. As a result, the green image will occupy the most part before the leaves, and the green part will become the observation area. When the yellow image becomes more than 20% through the HLS color separation as the leaves are processed, it is evaluated as the first autumn color, and when the yellow image is more than 80% through the HLS color separation, it is evaluated as the peak color.

On the other hand, the mapper area calculation unit 133 divides the map area into ten regions based on the trisected altitude from the normal of the observed region in the extracted observation region on the basis of the color extracted by the color extraction unit 132, . ≪ / RTI >

7 is a diagram illustrating a process of extracting a map area based on altitude in an image-based seasonal observation system according to an exemplary embodiment of the present invention.

As shown in FIG. 7, an observation area is set on the basis of the altitude, and yellow, red, and brown colored leaves are observed after being divided into 10 parts from the top of the observation area.

At this time, when the leaves are observed based on the altitude of the observation area, when the leaves are observed at the altitude of 20% or less at the top of the observation area, it is judged as the first autumnal condition. It will be judged to be in a climax.

In the present invention, a method of calculating the area of the map area in the entire observation area, a method of dividing the entire observation area into 10 equal parts, a method of calculating how far the map leaves the trisected area, or a combination thereof have.

That is, the map area calculation unit 133 calculates the map area by dividing the map area into ten regions based on the altitude of the touched area from the normal of the observation area in the extracted observation area, (134) judges that the maple is in the first colored state when the maple leaves are observed from the normal to the 20% of the altitude at which the maple leaves are divided into the tenths of the area, and when the maple area is at the 80% When a colored map is observed, it is judged that the map is at peak color.

FIG. 8 is a process flowchart of a seasonal observation method using an image-based seasonal observation system according to an embodiment of the present invention.

As shown in FIG. 8, an image of a region captured by a camera and collected through a network is subjected to an exception process for regions other than the maple leaves (rocks, evergreen communities) to extract an observation region necessary for observation of the maple leaves (S110). Next, a specific color model is applied to the extracted observation region to extract colors other than the color of the leaves and the colors of the leaves (S120). That is, in the case of green, the color of the leaves is not the color of the leaves, and the colors of red, yellow and brown are set as the colors of the leaves.

Next, the area for the entire observation area is calculated, and the area of the map area in the observation area is calculated (S130). In calculating the ratio of the leaves from the calculated area, the ratio of the total area of the map area to the area of the map area is calculated (S140).

Through such a process, color separation is performed by a color model on the basis of images photographed with respect to a specific mountain to extract the map area. If the map is over a certain ratio, the map can be evaluated for the first maple leaves and the maple leaves .

Since the degree of the progress of the colored leaves is affected by the weather or the environment, it is possible to predict the progress of the colored leaves more reflecting the weather conditions. It is also possible to predict how far the leaves will proceed in the future, while accumulating information about the respective speed of the individual leaves according to the kinds of trees. In other words, it is possible to accurately evaluate the current progress of the colored leaves through observation of the colored leaves, and it is possible to predict the progress of the colored leaves based on the information on the progress speed of the colored leaves according to the weather or the trees.

Therefore, in the image-based seasonal observation system according to the present invention, it is possible to provide foliage observation, maple ratio, map prediction, or a combination thereof.

As described above, the present invention relates to a system and method for evaluating a colored state of leaves through observation of a map of autumn leaves. In autumn, the degree of progress of colored leaves for each mountain is observed. In addition, it is possible to improve the convenience of travelers by predicting the progress of the colored leaves to be performed in the future, to help attract tourists to tourist destinations, and to provide information on maple leaves to disperse travelers to reduce traffic congestion.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the technical scope of the present invention is not limited thereto but that various changes and modifications may be made without departing from the scope of the present invention. It will be possible.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It should be understood that various modifications may be made by those skilled in the art without departing from the spirit and scope of the present invention.

100: Seasonal (colored leaves) observation system 200: Camera
300: user terminal 400: database
110: network interface unit 120: maple image collecting unit
130: a colored state monitoring unit 140: a user interface unit
150: storage interface unit 131: observation area extracting unit
132: live image extracting unit 133: maple area calculating unit
134:

Claims (8)

The method of claim 1, further comprising: extracting an observation area for a map of leaves from the map image, wherein the observation area is divided into a plurality of areas at a predetermined ratio based on altitude from the top of the observation area; An observation area extracting unit for extracting an area of a tree where a maple leaves is excluded as an observation area excluding a part unrelated to a maple including a combination;
A color extracting unit for extracting a color from the extracted observation area;
A mapper area calculating unit for calculating an area of a maple area having colored leaves on the extracted observation area based on the extracted color; And
The method according to any one of claims 1 to 3, further comprising the steps of: calculating a ratio of leaves from the area of the observation area to the calculated area of the leaves; Determining a first colored autumn state when the first colored area is observed up to the first point and determining that the calculated colored area of the colored map is a colored top when the second colored area is observed from the normal altitude to the extracted viewing area; / RTI >
Wherein the altitude at which the first colored leaves state at the first point and the peak colored state at the second point are determined can be variably set. The method according to claim 1,
Wherein the image-based seasonal observation system comprises:
A colored map image collecting unit for collecting colored map images from at least one colored map photographing camera; And
And a storage interface for storing information on the map image and the map information. delete The method according to claim 1,
Wherein the color extracting unit comprises:
Wherein the color space is extracted using a color model of at least one of RGB, HSV, HLS, CMYK, or CMY, and the color corresponding to the colored leaves includes yellow, red or brown. Observation system. The method according to claim 1,
The map area calculating unit calculates,
Wherein the entire observation area is composed of a map area and a green area, and the map area comprises a red area, a yellow area, a brown area, or a combination thereof. Based seasonal observation system. The method according to claim 1,
In the above-described colored state determination section,
Wherein the ratio of the area occupied by the foliage region in the entire observation region is expressed as a percentage. The method according to claim 1,
Wherein the image-based seasonal observation system comprises:
The weather condition of the area where the map image is photographed or the kind of tree corresponding to the map image,
Estimating the foliage traveling speed according to the confirmed weather condition or the kind of the tree by referring to the information about the foliage traveling speed according to the pre-stored weather condition or the type of the tree,
A map of the sky, a map of the map, a map of the map, a map of the map, a map of the map, a map of the map. The method of claim 1, further comprising: extracting an observation area for a map of leaves from the map image, wherein the observation area is divided into a plurality of areas at a predetermined ratio based on altitude from the top of the observation area; An observation area extracting step of extracting, as an observation area, an area of a tree to which a maple leaves is excluded, excluding a part not associated with a maple including a combination;
A color extracting step of extracting a color in the extracted observation area;
Calculating an area of a maple area having colored leaves from the extracted observation area based on the extracted color; And
The method according to any one of claims 1 to 3, further comprising the steps of: calculating a ratio of leaves from the area of the observation area to the calculated area of the leaves; Determining a first colored autumn state when the first colored area is observed up to a first point and determining a colored area as a colored top when the calculated first colored area is observed from a normal altitude to the extracted observation area to a second altitude; / RTI >
Wherein the altitude at which the first foliage condition of the first point and the foliage peak condition of the second point are determined can be variably set in the foliage condition determination step.

Images