JP7360872B2 - Reading device and program - Google Patents

Description

Embodiments of the present invention relate to a reading device and a program.

Traditionally, retail stores (stores) such as supermarkets read identification information such as JAN (Japanese Article Number) codes from code symbols (barcodes, two-dimensional codes) attached to products, and identify customers based on the read identification information. The sales of the products purchased by the customer are registered.

Furthermore, conventionally, there is a reading device that transports a product on a conveyance path such as a belt conveyor and reads identification information attached to the product with a reading unit such as an image pickup device installed in the middle of the conveyance path.

By the way, in the above-mentioned configuration for transporting products, the products placed on the transport path are transported to a receiving place such as a bagging area without being touched by store staff or customers, thereby saving the trouble of transporting the products by hand. be able to. However, there is a possibility that an operation to replace the product with another product may be performed while the product is being transported. When a product replacement operation is performed, there is a possibility that the product whose identification information has been read is different from the product that arrives at the receiving location, which poses a problem in that product sales cannot be registered correctly.

The problem to be solved by the present invention is to provide a reading device and a program that can more reliably register sales of products transported along a transport path.

The reading device of the embodiment includes a conveyance path, a reading section, an imaging section, an extraction section, and an output section. The conveyance path conveys the product. The reading unit reads identification information for identifying the type of the product from the product being transported along the transport path. The imaging units are provided upstream and downstream of the reading unit, respectively, and capture images of the product being conveyed along the conveyance path. The extracting unit extracts a feature amount representing a feature of the product from the captured image captured by each of the image capturing units. The output unit outputs the identification information read by the reading unit when the degree of similarity of the feature amount extracted by the extraction unit is equal to or greater than a threshold value.

FIG. 1 is an external perspective view showing an example of a product sales data processing system according to the first embodiment. FIG. 2 is a diagram showing an example of the hardware configuration of the reading device according to the first embodiment. FIG. 3 is a diagram showing an example of the functional configuration of the reading device according to the first embodiment. FIG. 4 is a flowchart illustrating an example of a reading process executed by the reading device of the first embodiment. FIG. 5 is an external perspective view showing an example of a product sales data processing system according to the second embodiment. FIG. 6 is a diagram illustrating an example of the hardware configuration of a reading device according to the second embodiment. FIG. 7 is a diagram showing an example of the data structure of product setting information according to the second embodiment. FIG. 8 is a diagram illustrating an example of the functional configuration of a reading device according to the second embodiment. FIG. 9 is a flowchart illustrating an example of a reading process executed by the reading device of the second embodiment.

Hereinafter, a reading device and a program according to an embodiment will be described with reference to the drawings. In the embodiment described below, an example will be described in which the present invention is applied to a product sales data processing system that can perform product sales registration and accounting processing. Note that the present invention is not limited to the embodiment described below.

FIG. 1 is an external perspective view showing an example of a product sales data processing system according to an embodiment. As shown in FIG. 1, the product sales data processing system 1 includes a reading device 10 and a product sales data processing device 20.

The reading device 10 is an example of a reading device. The reading device 10 is a device that performs processing for reading identification information that identifies the type of product H from a product H that a customer purchases. Specifically, the reading device 10 includes a product placement table 11, a base 12, a loading table 13, a belt conveyor 14, a reading section 15, and an imaging section 16.

The product placement stand 11 is a stand on which a customer temporarily places a product H to be purchased. The base 12 is a casing that connects the product placement platform 11 and the loading platform 13. The base 12 includes a belt conveyor 14 that moves from the product placement platform 11 toward the loading platform 13.

The loading platform 13 is a platform for bagging the products H transported by the belt conveyor 14. The product H conveyed by the belt conveyor 14 is pushed out and placed on the loading table 13. For example, the customer can bag the products H placed on the loading table 13.

The belt conveyor 14 forms a conveyance path for conveying the product H from the product placement table 11 toward the loading platform 13. Specifically, the belt conveyor 14 is driven by a drive unit 108 (see FIG. 2), which will be described later, and moves in the conveying direction of arrow A1 in the figure, that is, the direction along the Y axis.

The reading unit 15 is an example of a reading unit. The reading unit 15 reads identification information from the product H conveyed by the belt conveyor 14. Here, the identification information is, for example, a product code such as a JAN (Japanese Article Number) code, and means information that can identify the type of product H.

Note that the reading unit 15 can adopt a device configuration depending on the type of medium holding the identification information. For example, if identification information is held in a code symbol attached to the product H, the reading unit 15 can be implemented by a code scanner, an imaging device, or the like that can read the code symbol. For example, if identification information is held in a wireless tag such as an RFID (Radio Frequency IDentifier) tag attached to product H, it can be read with an RFID reader or the like that can read information from the wireless tag. Section 15 can be realized.

FIG. 1 shows a gate-shaped reading section 15 whose top and side surfaces are shielded. Here, for example, a reading device (not shown) such as a code scanner, an imaging device, or an RFID reader is attached to the top plate and vertical walls that constitute the gate. The reading device reads the identification information from the product H passing through the gate, with the reading direction facing toward the surface of the belt conveyor 14 or the like. Note that the reading section 15 is not limited to the gate shape, and may be arranged in the vicinity of the belt conveyor 14 with the reading device exposed.

The imaging unit 16 is an example of an imaging unit. The imaging unit 16 can be realized by an imaging device having an image sensor such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal-Oxide Semiconductor).

The imaging section 16 is arranged upstream and downstream of the reading section 15 in the conveyance direction of the belt conveyor 14, respectively, and images the product H conveyed by the belt conveyor 14. FIG. 1 shows an example in which the imaging section 16a is arranged upstream of the reading section 15, and the imaging section 16b is arranged downstream of the reading section 15. In addition, in FIG. 1, the imaging unit 16 is arranged at one end of both ends of the belt conveyor 14 along the conveyance direction, and the posture of the imaging unit 16 is fixed so that the imaging direction (the direction of the broken line arrow) faces the other end. ing. In this case, the imaging unit 16 mainly images the side surface of the product H conveyed by the belt conveyor 14.

It is assumed that the angles at which the image capturing units 16a and 16b image the product H being conveyed on the belt conveyor 14, that is, the postures of the image capturing units 16a and 16b with respect to the belt conveyor 14, are substantially the same. As a result, the angles and parts of the product H imaged by the imaging units 16a and 16b can be made substantially the same, so that the degree of similarity of the feature amounts described below can be efficiently determined.

The product sales data processing device 20 performs sales registration and accounting processing for the product H purchased by the customer based on the identification information read by the reading device 10. Specifically, the product sales data processing device 20 corresponds to the identification information read by the reading device 10 based on a product master that associates the identification information of each product with product information such as the product name and price of the product. Identify product information for a product. The product sales data processing device 20 registers sales of products by temporarily storing identification information read by the reading device 10 and product information corresponding to the identification information. Then, the product sales data processing device 20 calculates the total price of the product H purchased by the customer based on the product information of each product H whose sales have been registered, and settles the total price with the amount paid by the customer. Perform accounting processing.

Next, the configuration of the reading device 10 will be explained. FIG. 2 is a diagram showing an example of the hardware configuration of the reading device 10. As shown in FIG. 2, the reading device 10 includes a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, and a RAM (Random Access Memory) 103.

The CPU 101 is an example of a processor, and centrally controls the operation of the reading device 10. ROM 102 stores various programs. The RAM 103 is a workspace in which programs and various data are developed. The CPU 101, ROM 102, and RAM 103 are connected to each other via a bus 104. The CPU 101, ROM 102, and RAM 103 constitute a control unit 100 of a computer configuration. In the control unit 100, the CPU 101 executes various processes by operating according to a control program 105a stored in the ROM 102 or the storage unit 105 and developed in the RAM 103.

Further, the control unit 100 is connected to a storage unit 105 via a bus 104. The storage unit 105 is composed of an HDD (Hard Disc Drive), a flash memory, etc., and maintains the stored contents even if the power is cut off. The storage unit 105 stores, for example, a control program 105a. The control program 105a is a control program for controlling the reading device 10.

Further, a communication unit 106 is connected to the control unit 100 via a bus 104. The communication unit 106 is a communication interface connectable to a network such as a LAN (Local Area Network). The communication unit 106 is an example of an output unit. The communication unit 106 communicates with the product sales data processing device 20 to which identification information is output, a store server (not shown), an information processing device installed at a service counter in the store, and the like.

Further, the control unit 100 is connected to a driving unit 108 in addition to the above-described reading unit 15 and imaging unit 16 (16a, 16b) via a bus 104 and an input/output controller 107. The drive unit 108 controls the drive of the belt conveyor 14. Specifically, the drive unit 108 moves the product H in the conveyance direction (direction A1 in FIG. 1) by driving the belt conveyor 14 under the control of the control unit 100.

Next, the functional configuration of the reading device 10 will be explained. FIG. 3 is a diagram showing an example of the functional configuration of the reading device 10.

As shown in FIG. 3, the reading device 10 includes a reading result acquisition section 111, a feature extraction section 112, and an output control section 113 as functional sections. Some or all of these functional units may be a software configuration realized by cooperation between a processor (CPU 101) and various programs (for example, control program 105a) stored in memory (ROM 102, storage unit 105). good. Further, some or all of these functional units may be a hardware configuration realized by a dedicated circuit or the like.

The reading result acquisition unit 111 is an example of an acquisition means. The reading result acquisition unit 111 acquires the reading result of the reading unit 15. Specifically, the reading result acquisition unit 111 acquires the identification information read from the product H by the reading unit 15.

The feature extraction unit 112 is an example of an extraction unit and an extraction means. The feature amount extracting unit 112 extracts a feature amount indicating the appearance characteristics of the product H from the captured image of the product H captured by the imaging unit 16. Specifically, the feature extraction unit 112 acquires a captured image from the imaging unit 16 and detects an image area representing the product H included in the captured image.

For example, the feature extraction unit 112 extracts contour lines and the like from an image obtained by binarizing a captured image. Further, the feature extracting unit 112 detects the product H based on the difference between the contour line extracted from a background image prepared in advance and the contour line extracted from the captured image. Here, the background image is an image captured by the imaging unit 16 of a background that does not include the product H. Thereby, the feature extracting unit 112 detects the image area in which the product H is represented by extracting from the captured image a contour line that is not included in the contour line of the background image.

Further, the feature amount extraction unit 112 extracts the feature amount of the product H from the image area of the product H detected from the captured image. For example, the feature amount extracting unit 112 extracts feature amounts that are information obtained by parametrizing external features such as the shape of the product H, surface color, pattern, unevenness, and the like.

Note that the feature amount extraction unit 112 extracts feature amounts from the captured images captured by each of the imaging units 16a and 16b. Specifically, the feature extracting unit 112 extracts the feature from the captured image captured by the imaging unit 16a as the product H is conveyed on the belt conveyor 14, and then extracts the feature from the captured image captured by the imaging unit 16b. Extract features from images.

Hereinafter, the captured image captured by the imaging unit 16a will also be referred to as a first captured image, and the feature amount extracted from the first captured image will also be referred to as a first feature amount. Further, the captured image captured by the imaging unit 16b is also referred to as a second captured image, and the feature amount extracted from the second captured image is also referred to as a second feature amount.

The output control section 113 is an example of an output section and an output means. The output control section 113 controls the output of the identification information acquired by the reading result acquisition section 111 based on the comparison result between the first feature amount and the second feature amount extracted by the feature amount extraction section 112.

Specifically, the output control unit 113 compares the first feature amount and the second feature amount extracted by the feature amount extraction unit 112, and calculates the degree of similarity between the two feature amounts. Here, the degree of similarity is a physical quantity indicating how similar the product H represented by the first captured image is to the product H represented by the second captured image. The method for calculating the degree of similarity is not particularly limited, and known techniques such as general object recognition can be used.

After calculating the degree of similarity between the first feature amount and the second feature amount, the output control unit 113 compares the degree of similarity with a threshold value. Then, the output control unit 113 outputs the identification information acquired by the reading result acquisition unit 111 to the product sales data processing device 20 when the degree of similarity is greater than or equal to the threshold, and when the degree of similarity is less than the threshold, the output control unit 113 outputs the identification information acquired by the reading result acquisition unit 111 to the product sales data processing device 20. The output of the identification information acquired by the acquisition unit 111 is suppressed. Although the threshold value can be set arbitrarily, it is preferable to set it to a value such as 80% or 90%, which allows the identity of the product H to be determined.

Here, in order to confirm the identity of the product H whose identification information was read by the reading unit 15 and the product H imaged by the imaging units 16a and 16b, the output control unit 113 causes the reading result acquisition unit 111 to identify the product H by using the reading result acquisition unit 111. Based on the timing at which the information is acquired, the first feature amount and the second feature amount extracted before and after the timing are subjected to similarity determination.

For example, if the product H placed on the belt conveyor 14 is conveyed to the end of the belt conveyor 14 (the loading table 13) while maintaining its condition, the first captured image and the second captured image are the same product. H will be imaged. In this case, since the same product H is represented in the first captured image and the second captured image, the degree of similarity between the extracted first feature amount and second feature amount also becomes equal to or greater than the threshold value. Therefore, the output control unit 113 outputs the identification information read when the product H is transported to the product sales data processing device 20.

On the other hand, for example, if the product H placed on the belt conveyor 14 is replaced with another product H after passing through the reading unit 15, the first captured image and the second captured image differ from each other in the product H. will be imaged. In this case, since different products H are represented in the first captured image and the second captured image, the degree of similarity between the extracted first feature amount and second feature amount is less than the threshold value. will suppress the output of identification information.

Thereby, the reading device 10 can output the identification information of the product H to the product sales data processing device 20 when the identity of the product H can be confirmed during the conveyance process of the belt conveyor 14. Further, if the product H whose identification information has been read is replaced with another product H during transportation due to fraud or other reasons, the reading device 10 detects non-identity of the products H, Output of identification information can be suppressed.

Note that when the similarity of the feature amounts is less than the threshold, the output control unit 113 suppresses the output of the identification information and sends error information to the product sales data processing device 20 and other devices, thereby eliminating the error. The occurrence of this may be notified. Further, the output control unit 113 may stop the operation of the belt conveyor 14 by controlling the drive unit 108 when the similarity of the feature amounts is less than a threshold value.

The operation of the reading device 10 will be described below with reference to FIG. 4. Here, FIG. 4 is a flowchart showing an example of a reading process performed by the reading device 10. Note that this process is repeatedly executed while the belt conveyor 14 is operating.

First, when the product H is moved from the product placement table 11 to the belt conveyor 14 and conveyance by the belt conveyor 14 is started, the imaging unit 16a images the product H being conveyed. When the feature extraction unit 112 acquires the first captured image captured by the imaging unit 16a (step S11), it extracts the first feature from the first captured image (step S12).

Next, when the product H transported in the transport direction passes through the gate of the reading unit 15, the reading unit 15 reads identification information from the product H passing through its own gate. Along with this, the feature extracting unit 112 acquires the identification information read from the product H by the reading unit 15 (step S13).

Subsequently, when the product H that has passed through the gate of the reading section 15 is transported toward the loading table 13, the imaging section 16b images the product H that is being transported. When the feature extraction unit 112 acquires the second captured image captured by the imaging unit 16b (step S14), it extracts the second feature from the second captured image (step S15).

Subsequently, the output control unit 113 compares the first feature amount extracted in step S12 and the second feature amount extracted in step S15, and calculates the degree of similarity between both feature amounts (step S16). Next, the output control unit 113 determines whether the degree of similarity calculated in step S16 is greater than or equal to a threshold (step S17).

Here, if the similarity is less than the threshold (step S17; No), the output control unit 113 outputs the error information to the product sales data processing device 20 or the like (step S18), and then ends this process.

On the other hand, if the similarity is greater than or equal to the threshold (step S17; Yes), the output control unit 113 outputs the identification information acquired in step S13 to the product sales data processing device 20 (step S19) and ends this process.

As described above, the reading device 10 extracts the feature amount of the product H conveyed on the belt conveyor 14 from the captured images of the imaging units 16 arranged upstream and downstream of the reading unit 15. Then, the reading device 10 outputs the identification information read by the reading unit 15 to the product sales data processing device 20 when the degree of similarity of the extracted feature amount is equal to or greater than the threshold value.

Thereby, the reading device 10 can output only the identification information of the product H whose identity has been confirmed on the belt conveyor 14 to the product sales data processing device 20. Therefore, the reading device 10 can more reliably execute the sales registration of the product H in the product sales data processing device 20.

Further, when the similarity of the feature amounts is less than the threshold value, the reading device 10 suppresses output of the identification information read by the reading unit 15 and notifies an error. Thereby, the reading device 10 can suppress the output of identification information when a replacement operation of the product H is performed during transportation, and therefore can suppress the sales registration related to the product H. Therefore, the reading device 10 can more reliably execute the sales registration of the product H in the product sales data processing device 20.

Note that the above-described embodiment can be modified and implemented as appropriate by changing part of the configuration or function of the reading device 10. Therefore, some modified examples of the above-described embodiment will be described below as other embodiments. Note that, below, points that are different from the embodiments described above will be mainly explained, and detailed explanations of points that are common to those already explained will be omitted. Further, the modified examples described below may be implemented individually or in appropriate combinations.

(Modification 1)
In the above-described embodiment, the configuration is described in which one imaging unit 16 is disposed on the upstream side and one downstream of the reading unit 15, but the configuration is not limited to this. For example, a plurality of imaging units 16 may be arranged upstream or downstream of the reading unit 15. Note that in this case, the processing of steps S11, S12, steps S14, and S15 explained with reference to FIG. 4 shall be increased according to the number of imaging units 16 arranged. Further, it is assumed that the processing related to determining the degree of similarity in steps S16 and S17 is performed based on the feature amount obtained from the captured image of each imaging unit 16.

(Modification 2)
In the above-described embodiment, the sales registration is performed in the product sales data processing device 20. However, the configuration is not limited to this embodiment, and a configuration in which sales registration is performed using the reading device 10 may be adopted. In this case, the reading device 10 is assumed to include a functional unit (for example, a sales registration unit) that registers the sales of the product corresponding to the identification information, based on the identification information output by the output control unit 113.

Specifically, the sales registration unit registers the product corresponding to the identification information output by the output control unit 113 based on a product master that associates the identification information of each product with product information such as the product name and price of the product. Identify information. Then, the sales registration unit registers the sales of the corresponding product H by temporarily storing the identification information output by the output control unit 113 and product information corresponding to the identification information. In this case, the reading device 10 functions as a product registration device.

Further, in the above-described embodiment, the reading device 10 and the product sales data processing device 20 are separated, but the reading device 10 and the product sales data processing device 20 may be configured integrally. In this case, the integrated reading device 10 (or product sales data processing device 20) can perform sales registration and accounting processing for the product H based on the output result of the output control unit 113 described above.

[Second embodiment]
Next, a second embodiment will be described. Note that the same configurations as those in the first embodiment described above are given the same reference numerals and explanations are omitted.

FIG. 5 is a top view showing an example of a reading device according to the second embodiment. As shown in FIG. 5, the reading device 30 includes a product placement table 11, a base 12, a loading table 13, a belt conveyor 14, a reading section 15, and an imaging section 16.

Here, the reading device 30 includes an imaging section 16 on the downstream side of the reading section 15, as a difference from the configuration of the reading device 10 explained in FIG. The imaging unit 16 images the product H conveyed by the belt conveyor 14, similarly to the first embodiment described above.

FIG. 6 is a diagram showing an example of the hardware configuration of the reading device 30. As shown in FIG. 6, the reading device 30 has the same hardware configuration as the reading device 10 described in FIG. 2. Further, as a configuration specific to the reading device 30, one imaging unit 16 is connected to the input/output controller 107. The storage unit 105 also stores product setting information 105b.

The product setting information 105b is setting information that defines the correspondence between the identification information and feature amounts of the product H. The product setting information 105b has a data structure shown in FIG. 7, for example.

FIG. 7 is a diagram showing an example of the data structure of the product setting information 105b. As shown in FIG. 7, the product setting information 105b stores the product name, identification information, feature amount, etc. of each product H in association with each other. Here, the identification information is identification information for identifying the type of product H, and corresponds to the identification information read by the reading unit 15. Further, the feature amount is a feature amount extracted from the captured image of the product H. Here, the feature amount stored in the product setting information 105b is a captured image captured by the imaging unit 16, or an image captured under the same imaging conditions as the imaging unit 16 (imaging angle with respect to product H, depth of field, etc.). It is preferable that the information be extracted from the captured image.

FIG. 8 is a diagram showing an example of the functional configuration of the reading device 30. As shown in FIG. 8, the reading device 30 includes a reading result acquisition section 111, a feature extraction section 112, a product identification section 311, and an output control section 312 as functional sections.

Here, based on the identification information acquired by the reading result acquisition unit 111, the product specifying unit 311 specifies the feature amount of the product corresponding to the identification information. Specifically, the product identification unit 311 compares the identification information acquired by the reading result acquisition unit 111 with the identification information stored in the product setting information 105b, and determines the characteristics of the corresponding product H from the product setting information 105b. Determine the amount.

The output control section 312 is an example of an output section. The output control unit 312 outputs the information obtained by the reading result acquisition unit 111 based on the comparison result between the feature quantity extracted from the captured image of the imaging unit 16 by the feature quantity extraction unit 112 and the feature quantity specified by the product identification unit 311. control the output of identification information.

Specifically, the output control section 312 compares the feature amount extracted by the feature amount extraction section 112 and the feature amount specified by the product identification section 311, and calculates the degree of similarity between the two feature amounts. Further, the output control unit 113 compares the calculated degree of similarity with a threshold value, and outputs the identification information acquired by the reading result acquisition unit 111 to the product sales data processing device 20 when the degree of similarity is greater than or equal to the threshold value. Note that when the degree of similarity is less than the threshold, the output control unit 312 suppresses the output of the identification information acquired by the reading result acquisition unit 111, and issues an error notification or the like.

For example, when the product H placed on the belt conveyor 14 is conveyed to the end of the belt conveyor 14 (the loading platform 13) while maintaining its state, the feature amount corresponding to the identification information read by the reading unit 15 and the feature amount extracted from the image captured by the imaging unit 16 have similarity. In this case, since the degree of similarity between both feature quantities is equal to or greater than the threshold value, the output control unit 113 outputs the identification information read during transportation of the product H to the product sales data processing device 20.

On the other hand, for example, if the product H placed on the belt conveyor 14 is replaced with another product H after passing through the reading unit 15, the identification information corresponding to the identification information read by the reading unit 15 The feature amount and the feature amount extracted from the image captured by the imaging unit 16 are different. In this case, the similarity between both feature amounts is less than the threshold, so the output control unit 113 suppresses the output of the identification information.

Thereby, the reading device 30 can output the identification information of the product H to the product sales data processing device 20 when the identity of the product H can be confirmed during the conveyance process of the belt conveyor 14 . Further, if the product H whose identification information has been read is replaced with another product H during transportation due to fraud or other reasons, the reading device 30 detects non-identity of the products H, Output of identification information can be suppressed.

The operation of the reading device 30 will be described below with reference to FIG. Here, FIG. 9 is a flowchart showing an example of the reading process performed by the reading device 30. Note that this process is repeatedly executed while the belt conveyor 14 is operating.

First, when the product H is moved from the product placement table 11 to the belt conveyor 14 and conveyance by the belt conveyor 14 is started, the reading unit 15 reads identification information from the product H passing through its own gate. Along with this, the feature extracting unit 112 acquires the identification information read from the product H by the reading unit 15 (step S21).

Subsequently, when the product H that has passed through the gate of the reading section 15 is transported toward the loading table 13, the imaging section 16 images the product H that is being transported. When the feature amount extraction unit 112 acquires the captured image captured by the imaging unit 16 (step S22), the feature amount extraction unit 112 extracts the feature amount from the captured image (step S23).

Next, based on the identification information acquired in step S21, the product identification unit 311 identifies the feature amount of the product H corresponding to the identification information from the product setting information 105b (step S24).

Subsequently, the output control unit 312 compares the feature amount extracted in step S23 and the feature amount specified in step S24, and calculates the degree of similarity between both feature amounts (step S25). Next, the output control unit 312 determines whether the degree of similarity calculated in step S25 is greater than or equal to a threshold value (step S26).

Here, if the similarity is less than the threshold (step S26; No), the output control unit 312 outputs the error information to the product sales data processing device 20 or the like (step S27), and then ends this process.

On the other hand, if the similarity is greater than or equal to the threshold (step S26; Yes), the output control unit 312 outputs the identification information acquired in step S22 to the product sales data processing device 20 (step S28) and ends this process.

As described above, the reading device 30 extracts the feature amount of the product H conveyed on the belt conveyor 14 from the captured image of the image capturing section 16 arranged downstream of the reading section 15, and extracts the feature amount and the readout image. The feature amount of the product H corresponding to the identification information read by the section 15 is compared. Then, when the degree of similarity between both feature amounts is equal to or greater than the threshold value, the reading device 30 outputs the identification information read by the reading section 15 to the product sales data processing device 20.

Thereby, the reading device 30 can output the identification information of the product H whose identity has been confirmed on the belt conveyor 14 to the product sales data processing device 20. Therefore, the reading device 30 can more reliably execute the sales registration of the product H in the product sales data processing device 20.

Further, when the degree of similarity of the feature amounts is less than the threshold value, the reading device 30 suppresses output of the identification information read by the reading unit 15 and notifies an error. Thereby, when the product H is replaced during transportation, the reading device 30 can suppress the output of the identification information, and therefore can suppress execution of sales registration related to the product H. Therefore, the reading device 30 can more reliably execute the sales registration of the product H in the product sales data processing device 20.

Note that the above-described embodiment can be modified and implemented as appropriate by changing part of the configuration or function of the reading device 30. Therefore, some modified examples of the above-described embodiment will be described below as other embodiments. Note that, below, points that are different from the embodiments described above will be mainly explained, and detailed explanations of points that are common to those already explained will be omitted. Further, the modified examples described below may be implemented individually or in appropriate combinations.

(Modification 1)
In the above-described embodiment, a configuration in which the imaging unit 16 is arranged downstream of the reading unit 15 has been described, but the configuration is not limited to this. For example, the imaging unit 16 may be arranged upstream of the reading unit 15. Note that in this case, the order of the processing in steps S21 to S23 described with reference to FIG. 9 is changed depending on the arrangement order of the reading section 15 and the imaging section 16.

Note that the program executed by the reading device 10 (reading device 30) of each of the embodiments described above is provided as being pre-installed in a ROM or the like. The program executed by the reading device 10 (reading device 30) of each of the embodiments described above is a file in an installable format or an executable format and can be stored on a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital). It may be configured to be recorded and provided on a computer-readable recording medium such as Versatile Disk).

Furthermore, the program executed by the reading device 10 (reading device 30) of each of the above-described embodiments is stored on a computer connected to a network such as the Internet, and is provided by being downloaded via the network. It's okay. Further, the program executed by the reading device 10 (reading device 30) of each embodiment described above may be provided or distributed via a network such as the Internet.

Although several embodiments of the invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, changes, and combinations can be made without departing from the gist of the invention. These embodiments and their modifications are included within the scope and gist of the invention, as well as within the scope of the invention described in the claims and its equivalents.

1 Product Sales Data Processing System 10 Reading Device 11 Product Placing Table 12 Base 13 Loading Table 14 Belt Conveyor 15 Reading Unit 16, 16a, 16b Imaging Unit 20 Product Sales Data Processing Device 111 Reading Result Acquisition Unit 112 Feature Extraction Unit 113 Output Control Section 311 Product identification section 312 Output control section H Product

Special Publication No. 2004-535030

Claims (4)

A conveyance path for conveying products;
a reading unit that reads identification information for identifying the type of the product from the product transported on the transport path;
an imaging unit that is provided upstream and downstream of the reading unit and captures an image of the product being conveyed along the conveyance path;
an extraction unit that extracts feature quantities indicating characteristics of the product from the captured images captured by each of the imaging units;
When the degree of similarity between the feature amount based on the image captured by the upstream image capturing unit and the feature amount based on the image captured by the downstream image capturing unit extracted by the extraction unit is equal to or greater than a threshold, the reading unit an output unit that outputs the identification information read by the
A reading device comprising: The reading device according to claim 1, wherein the output unit suppresses output of the identification information and issues a notification when the similarity of the feature amounts is less than a threshold. The reading device according to claim 1, wherein each of the imaging units is arranged in substantially the same attitude with respect to the conveyance path. the reading device computer,
an acquisition unit that acquires identification information from a reading unit that reads identification information for identifying the type of the product from the product being conveyed on the conveyance path;
Extracting means that is provided upstream and downstream of the reading unit and extracts a feature amount representing the characteristics of the product from an image captured by an imaging unit that captures an image of the product being conveyed along the conveyance path;
When the degree of similarity between the feature amount based on the image captured by the upstream imaging unit and the feature amount based on the image captured by the downstream imaging unit extracted by the extraction unit is equal to or greater than a threshold, the acquisition unit Output means for outputting the acquired identification information;
A program to make it work.

Images