JP2002260166A - Information distribution device and information distribution system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information distribution device capable of easily performing determination even by a user with less knowledge and experiences. SOLUTION: Image processing is performed on image data D from an image pick-up means to extract meaningful information I associated with the image data. The meaningful information is distributed to a terminal 5 of a user 5' together with the picked-up image D or the appropriately processed image D'. The user can easily perform determination by referring to the meaningful information.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information distributing apparatus and an information distributing system, and more specifically, to traffic information and other traffic-related information using two-way wireless communication such as a mobile phone. Related to a delivery system.

[0002]

2. Description of the Related Art As general traffic information, there are a highway radio on an expressway and traffic information broadcast during general radio broadcasting. It is difficult to obtain necessary information when the user wants to listen to such information because the broadcasting place is limited (in the former case) or the broadcasting time is fixed (in the latter case). Was. Furthermore, the current information could not be obtained in real time.

In order to solve such a problem, a situation such as a traffic congestion point on a road is captured by a video camera, and the captured image data is stored in a server. Then, the image data stored in the server is distributed to a predetermined terminal via the Internet or the like. In other words, the user operates a terminal capable of displaying image data and accesses the server described above. Then, the user selects the image information obtained by imaging the point he wants to see. With this selection, the image data stored in the server is output to the display screen of the terminal.

Then, since the image data currently being picked up by the video camera is sequentially stored in the server, the image data being picked up by the terminal can also be distributed. Therefore, the user can acquire the state of a necessary place (a predetermined place where the video camera is installed) as image information when he / she wants to see it. Thus, the user can see the acquired image information and know the degree of congestion, the cause of the congestion, and the like.

[0005]

However, in the conventional system, much information can be obtained based on the distributed image data. However, in order to obtain such information, the user needs to look at the image data. You need to understand its contents. That is, to obtain useful information, the user needs some knowledge and experience. Furthermore, the effective use of the acquired information depends more on the knowledge and experience of the users, and it has been difficult for all users to acquire and utilize the correct information.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an information distribution apparatus and an information distribution system in which image information to be distributed can be easily used and a user having little knowledge and experience can easily make a decision. .

[0007]

An information distribution apparatus according to the present invention is an information distribution apparatus for distributing information to a user via a network. An information extracting unit that performs image processing on the image data from the imaging unit and extracts meaningful information attached to the image data; a unit that generates distribution image data from the image data; It is provided with distribution information generating means for generating distribution information by synthesizing data and the meaningful information, and communication means for outputting the distribution information to a network.

[0008] "Distributing information to a user" refers to not only a case where an information distribution device directly distributes information to a user's terminal, but also a case where information is transmitted once to another device and indirectly transmitted through that device. This includes the case of distribution to the user's terminal. The meaningful information is information suitable for making an accurate and prompt determination when making a determination from a distributed image.
If there is information that is difficult to determine from the image, information that takes time to make a determination or requires experience / knowledge is extracted as meaningful information in advance. In the embodiment, the information is displayed as character information, but may be various symbols.

The meaningful information extracting means may directly receive and process the image data sent from the imaging means, or may temporarily store the image data in the image storing means, read it out and process the image data. You may make it.
The means for generating the image data for distribution is, in the embodiment,
This is realized by the preprocessing unit 17a. It should be noted that although “generation of distribution image data” is described, it is not always necessary to perform processing on an image as in the embodiment. If the image data sent from the imaging means can be delivered as it is, processing such as selecting necessary image data without processing may be performed.

According to the present invention, when image data is distributed, meaningful information is also distributed. Therefore, the user who receives the image data can quickly view the meaningful information together with the image regardless of knowledge and experience. And accurate judgment can be made. Furthermore, since an image is sent as usual, various kinds of information that cannot be obtained from meaningful information can be obtained according to the ability of the individual.

[0011] In a preferred embodiment of the present invention, a sensor for acquiring information other than an image is provided, and the distribution information generating means has a function of synthesizing and outputting meaningful information obtained from the sensor. It is. of course,
Such a sensor or the like does not necessarily need to be provided. When the sensor is provided in this manner, information that is difficult to understand in an image can be distributed together, so that more accurate determination can be quickly performed.

Various kinds of meaningful information to be distributed are prepared. Therefore, all of the preset information may be distributed, or the distribution information generating unit may determine the type of meaningful information to be combined in response to a request received via the network. . In the latter case, only the information the user needs is sent,
This is preferable because there is no useless information for the user, and necessary information can be seen and determined immediately. In particular, if the terminal has a small display screen, if there is too much meaningful information to distribute, it will be difficult to see the image, which may hinder the judgment by looking at the image, but the problem of sending only the necessary ones is a problem. Will be resolved.

[0013] The imaging means is for imaging a road, and the meaningful information may be traffic-related information of the road. According to the field of use, traffic conditions and the like can be acquired in real time, which is useful when determining a traveling route. The traffic-related information includes various types of traffic-related information such as a running state of a vehicle such as a traffic jam and a state of a road surface or other roads.

In the information distribution system according to the present invention, information extraction means for performing image processing on the image data from the image pickup means and extracting meaningful information accompanying the image data, and image data for distribution from the image data , And a plurality of information distribution apparatuses including distribution information generating means for generating distribution information by synthesizing the distribution image data and the meaningful information. The information processing apparatus further includes an integrated processing device that receives information output from the plurality of information distribution apparatuses, integrates the information to generate integrated meaningful information, and outputs the integrated meaningful information to a network.

The information distribution devices do not necessarily need to be of the same type, but may have different functions. In addition, the information distribution device may of course add other functions, such as providing an external sensor, in addition to the functions described above. By generating integrated meaningful information by performing integrated judgment in this way, more complex and sophisticated information can be distributed.

The above-described components of the present invention can be combined as much as possible. Each means constituting the information distribution apparatus according to the present invention can be realized by a dedicated hardware circuit, or can be realized by a programmed computer.

[0017]

FIG. 1 shows an example of an entire information distribution system using a network to which the present invention is applied. As shown in FIG.
The server 2 is connected to a network 3 such as the Internet, and sequentially transmits images and other information collected by the information collection device 1 to the server 2 via the network 3. The transmitted information is processed and arranged on the server 2 and converted into a form suitable for distribution.

Further, the user connects the terminal 5 to the network 3 to download the information collected by the desired information collecting device 1 to the terminal 5 and acquire the information. That is, the server 2 distributes the stored predetermined information to the user's terminal 5 via the network 3 in response to a request issued from the user (terminal).

Therefore, the user can acquire the information collected by the information collecting device 1 at any time in an environment and a state where the user can connect to the network 3. Thus, by operating the information collection device 1 to transmit and accumulate the acquired information to the server 2 in real time, the user can always acquire necessary information and make a determination at any time.

The information collecting device 1 is provided around a road and includes an image pickup device for picking up an image of the condition of the road where the information is set. Specifically, it is as shown in FIGS. As shown in FIG. 1, the imaging device 10 includes a video camera using a CCD, and captures a moving image of a congested state of an installed peripheral road or a state of an intersection.
It is output as digital data (digital moving image information) such as nJPEG format. The outputted digital moving image information is provided to the data processing device 11.

An image pickup device 10 comprising a video camera picks up an image of a road condition in a monitoring area to obtain moving image data. Then, this photographing process operates to carry out the flowchart shown in FIG. That is, the imaging device 10 has an internal timer, and captures an image with the CCD camera every time a specified time (imaging interval) elapses (ST11 to ST13).
The image taken here is assumed to be a moving image, and the resolution is 7
This is a relatively high-resolution image that satisfies 20 × 480 pixels. The shooting interval is, for example, 30 frames / second. The image data photographed at predetermined intervals in this manner is converted into digital data (ST14), and the obtained image data is temporarily stored in an image temporary storage device (ST15) and transferred to the data processing device 11. . The photographing process repeatedly executes the above process.

The data processing device 11 has a normal PC level processing capability, processes digital moving image information photographed by the imaging device 10, extracts information which can be easily used, compresses the information, and performs unnecessary processing. By deleting data or the like, the data amount is changed to a data amount that can be easily distributed to a terminal connected to a network having a small line capacity.

The data processing device 11 is connected to a storage 12 constituted by a hard disk or other storage medium, and stores images processed by the data processing device 11 and data for processing. As data for such processing, an image is taken by the imaging device 10,
The image may be an image for comparison with the transmitted image to be processed, an image with a changed resolution, extracted data, or the like.

The image and other information processed by the data processing device 11 are provided to the communication device 13.
The communication device 13 transmits the acquired image and other information to the network 3. That is, the destination server 2
By generating a transmission frame or the like to which the above-mentioned address is added and transmitting it on the network 3, the above-mentioned processed image and other information are collected and stored in the server 2.

The internal configuration of the data processing device 11 is as shown in FIG. That is, it has an input unit 15 that receives output data of the imaging device 10 and obtains information received via the communication device 13. The information (data) obtained by the input unit 15 is provided to the CPU 17.

The CPU 17 reads out predetermined data stored in the external storage device (storage) 12 and appropriately uses the memory 14 as a work memory.
A predetermined processing is performed on the image data received from the input unit 15. Then, the generated processing data is passed to the output unit 16. The output unit 16 passes the received processed data to the communication device 13 so that the data can be transmitted. The processing units are connected to a bus and transfer data via the bus. Further, the data processing device 11 and the communication device 13 can be realized by, for example, a personal computer.

Here, in the present invention, as shown in FIG. 4, the processing in the data processing device 11 is not a simple image processing, but is a process in which acquired image data D or pre-processed image data obtained from the image data D is processed. Feature extraction is performed based on D ′ to generate meaningful information I. Actually, in consideration of transmission on the Internet, an image to be distributed is pre-processed as image data D 'whose data capacity is reduced. The feature extraction is performed based on the image data D (or D 'corrected for clarity). Then, the image data (D ') and the meaningful information I are paired and distributed. That is, the meaningful information I extracted from the image is distributed simultaneously with the image. Actually, the associated image data D 'and meaningful information I are stored in the server 2, and the user 5' accesses the server 2 to access the image data D 'related to the terminal 5 and the meaningful information I.
Download and display.

Then, the user 5 'makes a final decision while looking at the displayed image data D' and the meaningful information I. At this time, since the meaningful information I is displayed together with the image, even if there is little experience or knowledge necessary for making a judgment,
Accurate determination can be made easily and quickly based on the meaningful information I. In addition, as the content of the judgment,
For example, "change the route because it's getting jammed,""it's crowded now, but by the time you arrive at the location, the jam is gone, so let's go on the same route."
Etc.

FIG. 6 shows a software configuration of the CPU 17 for extracting the meaningful information I described above. That is, since image data is transferred from the imaging device 10 one frame at a predetermined interval, the CPU 17
Acquires such image data (photographing data) via the input unit 15. Specifically, it is provided to the preprocessing unit 17a. Further, the image data is also stored in the external storage device (storage) 12 as it is.

In order to correctly extract meaningful information, the imaging device 10 captures highly accurate image data. As a result, the capacity required for one frame increases, and if it is left as it is, it becomes difficult to distribute moving images on the premise of the Internet. Therefore, the preprocessing unit 17a executes a process of reducing the number of colors to be expressed so as to be able to deliver a moving image on the premise of the Internet, or reducing the resolution and the frame rate. Further, processing is performed to make the unclear portion of the image easier to see, and to improve the contrast and focus and to improve the dynamic range of light and dark. The preprocessed image data is temporarily stored in the storage 12 and used for other operations and image distribution.

In this example, the process is executed for all the image data that has been imaged and transferred. For example, for an image required when a distribution request is received and information is actually distributed, It may be performed. In such cases,
For example, it can be implemented by the procedure shown in the flowchart shown in FIG. In other words, when the request image data is received,
A required image is obtained from the storage (temporary image storage device) 12 (ST21, ST22). If there is no suitable image, the process jumps to step 1 and waits for an input accompanying transfer of a new image (ST23).

When a suitable image is available, the number of colors can be changed,
Perform image processing such as changing the resolution (ST24, ST2)
5). It is determined whether the request received in step 21 is a moving image (ST26). If the request is a moving image, necessary images are collected (ST27). For this necessary image, the number of colors, the resolution, etc. are changed. Then, the format is changed (ST28). Note that image data generated by changing this format (delivery image data)
May be temporarily stored in, for example, a distribution image data storage unit in the storage 12, or the distribution information generation unit 1
7c.

The information extracting section 17b for extracting meaningful information extracts the photographed image data stored in the storage 12, and extracts meaningful information therefrom. Specifically, the flowchart shown in FIG. 8 is performed.

That is, as shown in FIG. 1, the data processing device 11 stores the high-precision image data transferred from the imaging device 10 in the storage 1 as a temporary image storage device.
2 (ST31). Then, a necessary portion in the image is cut out (ST32). This cutout cuts out the roadway portion in the image, for example, based on the roadway range data stored in the storage 12 or the like.

Then, a moving object is detected from the clipped image (ST33). The detection of the moving object can be performed by using a “background difference method” or a “time difference method” provided as a general vehicle extraction algorithm.
That is, in the background subtraction method, a moving object is detected by preparing an image (background image) without a vehicle or a falling object in advance, and calculating the difference between the background image and the image to be processed. Also,
The time difference method extracts an object moved between the two images by performing a comparison operation on different images during the time interval δ.

Of the above two vehicle extraction algorithms,
Either one may be used, but each has advantages and disadvantages, and therefore, in the present embodiment, both are adopted and appropriately switched and extracted according to the situation. That is, the background subtraction method is suitable for detecting a moving object and a stationary object (for example, a vehicle that is temporarily stopped), but the detection accuracy is caused by the accuracy of the background image. If there is such a fluctuation, the reliability of the background image is reduced. That is,
Poor response to environmental change. On the other hand, in the time difference method, there is a problem that although it is possible to respond to environmental changes and extract a moving object with high accuracy, it is not possible to extract a stationary object. Therefore, the presence / absence (degree) of the environmental change is determined, and if the change is small, the extraction is performed by the background difference method, and if the change is large, the extraction is performed by the time difference method.

Next, a vehicle is specified from the extracted moving objects, and the number of vehicles passing therethrough is counted (ST34).
Then, the number of passing vehicles is output as character information. Actually, it is stored together with the counted date and time data in the passing number storage unit in the storage 12.

The counting of the number of vehicles can be dealt with, for example, by the following algorithm. A rectangular passing vehicle detection area is set at a predetermined position in the cut-out area. The size of this rectangle allows the front of the vehicle to enter and is installed for each lane. Then, by utilizing the fact that the front surface of the vehicle has many horizontal edges, a differential filter is applied to the passing vehicle detection area. As a result, when the extracted moving object is a vehicle and the front of the vehicle passes through the area, a peak appears in the output of the differential filter. Therefore, the presence or absence of the vehicle is determined based on the presence or absence of the peak. Then, the number of detected vehicles (the number of peaks) per unit time is the required number of passing vehicles.

Further, the speed of the vehicle is measured by tracking the vehicle (ST35). Then, the vehicle speed is output as character information. Actually, it is stored together with the measured date and time data in the vehicle speed storage unit in the storage 12.

This vehicle speed measurement can be dealt with, for example, by the following algorithm. That is, a speed measurement area is set for each lane. This speed measurement area is set to correspond to a fixed distance (a distance sufficiently longer than the length of one vehicle) along the lane. Then, the vehicle moving in this area is tracked. And
The travel distance is calculated from the position where the tracking of the vehicle has started and the position where the tracking has ended, and the speed is calculated from the time during which the vehicle was tracked.

In actual tracking, for example, a vehicle to be tracked is detected by a vehicle detection algorithm similar to the number counting algorithm further upstream from the above-mentioned area, and image data of the vehicle is registered as a template. Then, template matching is performed on the image data that enters and exits thereafter, and when it is detected that a vehicle that matches the template has entered the above-described area, the vehicle is tracked. The tracking of the vehicle can be executed by assuming the moving direction of the vehicle and performing template matching on the assumed area.

Further, the congestion distance is calculated from the number of vehicles and the speed obtained as described above (ST36). And
The obtained congestion distance is output as character information. actually,
It is stored together with the date and time data in the congestion information storage unit in the storage 12.

The calculation of the congestion distance can be dealt with, for example, by the following algorithm. That is, for example,
When the traveling speed is high, it can be estimated that no congestion has occurred. Further, even when the traveling speed is extremely low, if the number of vehicles passing through within a certain period of time is extremely slow, it can be said that the vehicle accidentally traveled slowly and no traffic congestion has occurred. On the other hand, even when the speed is low, if a certain number of vehicles have passed, it can be estimated that congestion has occurred. Further, as a characteristic of the traveling state (speed) of the vehicle during traffic congestion, stop and start are repeated, so that it can be estimated that traffic congestion occurs even when the speed changes frequently within a low speed. Furthermore, in the case of traffic congestion, it can be estimated that the longer the time of stoppage and the lower the speed, the longer the congestion distance. Therefore, a table in which traffic congestion distances are associated with the traveling conditions (input conditions) of the vehicle such as the number of passing vehicles and the speed is created in advance, and stored in the storage 12 or the like.
In the calculation processing in step 36, the value can be obtained by referring to the table.

Of course, besides this, for example, a plurality of cameras may be installed along the road, the head and the tail of the congestion may be determined, and the congestion distance may be calculated from the distance therebetween.

Further, from the time-series data of the traffic congestion distance, it may be determined whether the traffic congestion is currently progressing / expanding or going to be resolved, and may be stored. For example, the average of the number of traffic congestion distances in the past can be set to 0%, + X% when increasing,-% when decreasing, and the like. The congestion distance of the comparison standard is the average in the above example,
You may make it compare with the traffic jam distance of a round. Further, the congestion distance after a certain period of time may be predicted from the trajectory of the change in the congestion distance.

Further, the meaningful information to be extracted includes, in addition to the above-mentioned meaningful information, for example, the direction, interval,
Calculates the ratio of vehicle types based on the size of the high-density vehicle, determines the brightness of the shooting range by taking into account information from the camera that is shooting, The lighting rate and the like can be measured.

The distribution information generation unit 17 c
The meaningful information obtained in b and the image data processed by the preprocessing unit 17a are integrated and distributed. Specifically, the flowchart shown in FIG. 9 is implemented. In other words, it waits for a distribution request (ST41, ST42), and if so, reads out the corresponding distribution image data from the distribution image data storage unit in the storage 12 (ST43).

It is determined whether or not there is character information to be synthesized (usually). If there is, the corresponding character information, that is, meaningful information is read (ST44, ST45). At this time, the type of meaningful information to be read may be fixed in advance, or necessary information may be read according to a condition sent together with a distribution request from the user.

Then, the read character information and the preprocessed distribution image data are combined, and the obtained distribution image (with character information) is output (ST46, ST47). The output destination of the distribution image is, for example, the communication device 13 via the output unit.
The message may be transmitted to the network as it is, or may be temporarily stored in the storage 12 once and then transmitted. It should be noted that a video to be distributed is basically a live video with a small delay, and information is provided without losing the real-time property.

Thus, for example, the above information and the image itself can be integrated, and information distribution according to the user's request received through the network can be performed. For example, as shown in FIG. 10, conventionally, only an image obtained by capturing the state of the road in the monitoring area is provided.
According to the present embodiment, as shown in FIG. 11, character information is also displayed on the display screen of the terminal 5. By transmitting the video data and the data extracted from the video according to the request of the user in this manner, it is possible to easily receive information that is difficult to determine only with the video.

The above-described detection of a moving object (vehicle) and processes associated therewith are described in, for example, "Development of Traffic Flow Monitoring Image Processing System" (OMRON TECHNIC).
SVol. 38 No. 1 1998 10th-13th
Page) and “Real-time traffic flow measurement system using image processing” (Mitsubishi Heavy Industries Technical Report Vol 34 No. 6 (19)
97-11), pp. 418 to 421).

Further, a user who wants to obtain such information,
It is often in a vehicle, such as a normal driver or a passenger. Therefore, the display screen of the terminal 5 is often small, such as a mobile phone or a similar mobile terminal. Moreover, since the image data has a reduced resolution or a reduced number of colors, it may be difficult to determine the image data using only the image, even if the user has the experience and knowledge. In addition, even a terminal having a small display screen can easily and quickly understand, and can make necessary judgments correctly.

It should be noted that the same effect can be obtained if the imaging device 10 can take a moving image other than the video camera. Further, if an infrared camera is used in addition to ordinary CCD visible light, not only daytime but also nighttime shooting and an image corresponding to a temperature difference can be taken. further,
As for the resolution of the image, the frame rate may be set to a setting suitable for the information to be provided, and is not limited to the above method.

In this embodiment, the image pickup device and the data processing device are connected. However, these connections do not need to be wired. For example, as shown in FIG.
The same effect can be obtained by connecting the transmitting device 18 to the (camera unit), transmitting data wirelessly, receiving the data remotely by the receiving device 19, providing the image data to the data processing device 11, and processing there. can get.

The storage 12 may use a storage device other than the HDD. Furthermore, a configuration in which the functions are limited and the storage is omitted if there is no need to temporarily store captured images is also possible. Network 3
The same effect can be obtained by a distribution method using not only the Internet but also other methods such as a local network and a wireless LAN.

In addition to the above-mentioned methods for extracting information from an image, the depth of field of view can be calculated by using the white balance or transparency index of the photographed image, or by extracting a specific object from the image to obtain information other than the vehicle. It is possible to grasp the abnormal situation in the image by counting the number of objects and searching for a blinking object. In addition, by comparing images captured from the same position at different times, it is possible to detect different portions in the current image or to grasp changes in the situation.
Further, the imaging apparatus 10 can use not only a fixed fixed point but also a camera that operates according to pre-programmed movement or a user's request.

In this example, the information collected by the individual information collecting apparatuses 1 is provided to the server 2 via the network 3 once, but the present invention is not limited to this. A server function is provided, and each user can use an information collection device 1 installed at a place where information is to be collected.
May be directly accessed to acquire information. In this case, for the convenience of the user, the server 2 in the system configuration shown in FIG. 2 may be used as a portal site.

FIGS. 13 to 15 show a second embodiment of the present invention. As shown in the figure, based on the first embodiment, an external sensor 20 is further provided, and the sensor output of the external sensor 20 is also sent to the data processing device 11. The external sensor 20 measures, for example, environmental information such as temperature (temperature in this example).

The software configuration in the CPU 17 of the data processing device 11 is as shown in FIG. 14, and the sensor data processing unit 1 for processing sensor information from the external sensor 20
7d.

The sensor data processing section 17d generates data to be provided as meaningful information based on the acquired sensor information (additional information). In other words, it has a function of converting the content represented by the sensor output into character information.
For example, when the external sensor 20 is a temperature sensor, the detected temperature is recognized, character information such as “air temperature X ° C.” (X is an actual temperature) is generated, and stored in the sensor information storage unit in the storage 12. I do.

Further, it has a function of generating meaningful information based on the sensor. As an example, by obtaining information on the temperature, information on icing on the road can be obtained. For example, when the temperature is low, it is possible to generate caution information such as "freezing caution". Actually, a table in which the temperature and the contents to be displayed are associated with each other is created, and the table can be obtained by the table reference method.

Then, the distribution information generation unit 17c adds the information extraction unit 17b to the image data generated by the preprocessing unit 17a.
In addition, a distribution image is generated and output by synthesizing the meaningful information (character information) generated by the sensor data processing unit 17d.

Thus, for example, it is possible to distribute information as shown in FIG. In this example, the caution information of "freezing caution" determined from the temperature and the information is distributed.

With such a configuration, information from other sensors can be obtained simultaneously with image information. Further, using the information obtained from the external sensor 20, the image data can be processed or the accuracy of the information extracted from the image data can be increased.

In this embodiment, the temperature is used for the traffic information by using the temperature sensor.
Data that can be used through the Internet include weather information such as wind power, humidity, rainfall, seismic intensity, and wave height, the exact position of the camera using GPS, position information such as the direction and height of the target, and the type of vehicle. More detailed information can be provided by transmitting information using discrimination, license plate read information, and the like. That is, various kinds of distributable information can be prepared as shown in FIG.

The size of the object, the moving speed, and the like are calculated from information such as the aperture and shutter speed of the camera used for shooting, the shooting direction, the type of lens, the pan and tilt speed, the resolution of the CCD, and the shot image. can do. Thus, it can be used also as auxiliary data when extracting other meaningful information.

Further, by obtaining geographical information of a range to be photographed in advance and mapping it to a photographing point, it is possible to know an accurate distance and a moving direction with respect to the object. Further, by distributing an image corresponding to personal privacy and security, it is possible to mask a part of the image and keep it private when the image is distributed. Note that the other configuration and operation and effect are the same as those of the above-described first embodiment, and therefore, corresponding members are denoted by the same reference numerals and detailed description thereof will be omitted.

FIGS. 18 and 19 show a third embodiment of the present invention. This embodiment is based on the second embodiment. As shown in the figure, each image data D ′ and meaningful information I collected and generated by a plurality of information collecting devices 1 are once collected and integrated by an integrated processing device 21. Then, the integrated integrated meaning information is distributed. As described above, by having a plurality of devices for collecting final distribution information, more complicated data processing becomes possible, and it becomes possible to analyze and obtain data that could not be obtained in one place. As the integrated meaningful information, for example, accurate congestion information (congestion distance, whether or not congestion is being resolved, and the like) can be obtained from meaningful information at a plurality of locations.

More specifically, for example, in the case of traffic jam information, information is extracted as to which direction of the actual road image and which direction of the lane determined from the image are and how much traffic is flowing. With one information collecting device, only the flow of one observation point can be known. However, if all the information collecting devices are installed at each intersection along a certain road, the traffic congestion information at each intersection can be known. By collecting this in the integrated processing device, it becomes possible to distribute road information linked to the map. this is,
Record the position of each information processing device in the integrated processing device,
This is made possible by collecting each image and integrating it with information indicating the location on the map.

Further, the start and end positions of the traffic jam can be specified. This is made possible by collecting information along the road in sequence. The integrated processing device can obtain more useful information by receiving the image and the meaningful information and also integrating the information of each information collecting device itself.

Although the above example is based on traffic congestion information, simply integrating meaningful information from a plurality of information collecting devices,
New meaningful information can be extracted simply by calculating the distribution of the state. For example, by extracting information on the number of people at each sightseeing spot and the number of people at shopping spots as meaningful information, it is possible to extract information on the number of people at that day and spots that are more vacant.

This is made possible by the fact that the meaningful information converts image information into information which can be more easily processed by a computer. Actually, it is possible to extract information that makes effective use of the extraction source image by performing a simple sort, aggregation, or other arithmetic processing.

In the example of FIG. 18, the integrated processing device 21
And the respective information collecting apparatuses 1 are shown to be directly connected by a communication line. However, the form of information transmission may be of course through a network. Although the present embodiment is based on the second embodiment, the integrated processing device 2
1 is connected to the first information collecting device 1 having no external sensor.
The above-described embodiment may be used, or both may be mixed.

FIGS. 20 to 22 show a fourth embodiment of the present invention. In the present embodiment, the function of the information extracting unit 17b is changed based on the first embodiment. That is, in the vicinity of the intersection, the traveling state is controlled by the state of the traffic light. Naturally, when the traffic lane is at a red light, the vehicle stops. Therefore, when the vehicle is stopped, it is necessary to determine that the traffic is not congested. On the other hand, when the vehicle does not run despite the green light, it can be estimated that there is traffic.

Therefore, in the present embodiment, the function of the information extracting unit 17b is as shown in the flowchart of FIG. That is, as apparent from comparison with FIG.
To 39 are added, and the other processes are common. Specifically, when image data to be processed (see FIG. 21) is read (ST31), a signal portion (R1 in FIG. 22) in the image is cut out based on the signal portion data (ST37). Then, by observing the change in color and brightness in the cut-out region, it is determined whether the state of the signal at the time of shooting, that is, whether the color of the signal is "blue" (ST38, ST38).
39).

If the traffic light is not green, accurate traffic information cannot be obtained, so that the process returns to step 31 and shifts to the processing of the next image data. Then, only for the image data in the case of "blue", the number of vehicles after step 32,
Find speed, congestion distance, etc. Note that the other configuration, operation, and effect are the same as those of the above-described embodiments, and thus detailed description thereof will be omitted.

[0077]

As described above, according to the present invention, meaningful information is distributed together with an image, so that the image information to be distributed can be easily used, and even if the user has little knowledge and experience, judgment can be made. It can be done easily.

[Brief description of the drawings]

FIG. 1 is a diagram illustrating an example of an information distribution system to which a first embodiment of the present invention is applied.

FIG. 2 is a diagram showing an internal structure of an information collection device (information distribution device) according to the first embodiment of the present invention.

FIG. 3 is a diagram illustrating an internal structure of an information collection device (information distribution device) according to the first embodiment of the present invention.

FIG. 4 is a conceptual diagram (information and information) of the first embodiment according to the present invention.
FIG.

FIG. 5 is a diagram illustrating an operation of the imaging device.

FIG. 6 shows a main part of the internal structure of the data processing device 11 (mainly C
FIG.

FIG. 7 is a flowchart illustrating functions of a preprocessing unit.

FIG. 8 is a flowchart illustrating a function of an information extraction unit.

FIG. 9 is a flowchart illustrating a function of a distribution information generation unit.

FIG. 10 is a diagram illustrating an operation (a captured image).

FIG. 11 is a diagram illustrating an operation (a display image on a terminal).

FIG. 12 is a diagram showing a modification.

FIG. 13 is a diagram illustrating an internal structure of an information collection device (information distribution device) according to a second embodiment of the present invention.

FIG. 14 is a diagram showing the concept (flow of information and data) of the second embodiment according to the present invention.

FIG. 15 is a diagram showing a main part (mainly a CPU) of an internal structure of the data processing device 11;

FIG. 16 is a diagram illustrating an operation (a display image on a terminal).

FIG. 17 is a diagram illustrating types of distribution information.

FIG. 18 is a diagram illustrating an internal structure of an information collection device (information distribution device) according to a third embodiment of the present invention.

FIG. 19 is a diagram showing a concept (flow of information and data) of a third embodiment according to the present invention.

FIG. 20 is a flowchart illustrating a function of an information extraction unit that is a main part of the fourth embodiment according to the present invention.

FIG. 21 is a diagram illustrating an operation (a captured image).

FIG. 22 is a diagram illustrating an operation.

[Explanation of symbols]

 Reference Signs List 1 information collection device 2 server 3 network 5 terminal 5 'user (user) 10 imaging device 11 data processing device 12 storage (external storage device) 13 communication device 15 input unit 16 output unit 17 CPU 17a preprocessing unit 17b information extraction unit 17c Distribution information generating unit 17d Sensor data processing unit 18 Transmitting device 19 Receiving device 20 External sensor 21 Integrated processing device

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) H04N 7/173 610 G08G 1/00 A // G08G 1/00 1/09 A 1/09 H04B 7/26 M (72) Inventor Shinichi Mukogawa 801 Shidoji Horikawa Higashiiri Minamifudo-cho, Shimogyo-ku, Kyoto-shi, Kyoto Inside Omron Co., Ltd. 801 No. Jido-cho OMRON Corporation (72) Inventor Masaru Mitsuda 801 Minami-Fuji, Shimogyo-shi, Shimogyo-ku, Kyoto CA16 CB01 CB08 CB12 CB16 CB19 CC01 DA07 DA12 DA13 DA20 DB02 DB06 DB09 DC30 DC36 5C022 AA01 AC42 5C064 BA07 BB10 BC18 BC23 BD02 BD08 5H180 AA01 BB02 CC05 DD02 DD04 DD08 DD09 EE03 5 K067 AA21 BB04 DD52 EE02 EE16 FF02 FF23 HH23 KK15

Claims (5)

[Claims] 1. An information distribution device for distributing information to a user via a network, wherein the information extraction device performs image processing on image data from an imaging unit and extracts meaningful information attached to the image data. Means for generating distribution image data from the image data; distribution information generating means for synthesizing the distribution image data and the meaningful information to generate distribution information; and outputting the distribution information to the network. An information distribution device comprising communication means. 2. The apparatus according to claim 1, further comprising: a sensor for acquiring information other than an image, wherein the distribution information generating means has a function of combining and outputting meaningful information obtained from the sensor. An information distribution device according to claim 1. 3. The information distribution apparatus according to claim 1, wherein the distribution information generation unit determines a type of the meaningful information to be combined in response to a request received via the network. 4. The apparatus according to claim 1, wherein the image capturing unit captures an image of a road, and the meaningful information is traffic-related information of the road. Information distribution device. 5. An information extracting unit for performing image processing on image data from an imaging unit and extracting meaningful information attached to the image data, a unit for generating distribution image data from the image data, A plurality of information distribution devices including distribution information generating means for generating distribution information by synthesizing distribution image data and the meaningful information; receiving information output from the plurality of information distribution devices; An information distribution system including an integrated processing device that generates semantic information and outputs the integrated meaningful information to a network.