JP5798175B2 - Information processing apparatus, store system, and program - Google Patents

Description

  Embodiments described herein relate generally to an information processing apparatus, a store system, and a program.

  Conventionally, a feature amount of a target article is extracted from image data obtained by imaging an object (object) as a target using an image sensor device, and the degree of similarity is compared with comparison data (feature quantity) in a dictionary prepared in advance. There is a technology related to general object recognition that calculates and recognizes (detects) the type or the like of the article according to the calculated similarity. Further, there has been proposed a store system that uses the technology related to general object recognition to identify products such as fruits and vegetables and registers sales of products recognized as objects.

  However, in a commodity reading device (information processing device) and a checkout system (store system), an engine used for object recognition processing is always operated. Therefore, there is a problem that the CPU is always loaded even when the object recognition process is unnecessary.

The information processing apparatus according to the embodiment includes a capturing unit that captures a frame image including an image of an object captured by the imaging unit, an image of the object captured by the imaging unit, and a reference image of each registered product registered in the dictionary. And executing a recognition process for extracting the candidate for the registered product corresponding to the imaged object based on the similarity indicating how similar to the captured object. When a change in the color attribute of the frame image is detected and the color attribute exceeds a predetermined reference value, the means for executing the recognition process is activated, and the color attribute changes after a predetermined time has elapsed. If there is no, the recognition process is not executed .

The store system according to the embodiment includes an imaging unit, a capturing unit that captures a frame image including an image of the object captured by the imaging unit, an image of the object captured by the imaging unit, and each registration registered in the dictionary. Means for executing a recognition process for extracting a candidate for the registered product corresponding to the imaged object based on a similarity indicating how similar the reference image of the product is; and a candidate for the registered product Sales registration processing means for performing sales registration processing of the registered product in the case of one, or one registered product selected in the case where there are a plurality of candidates for the registered product, When a change in the color attribute of the frame image is detected and the color attribute exceeds a predetermined reference value, the means for executing the recognition process is activated, and the color attribute changes after a predetermined time has elapsed. If there is no The recognition process is not executed.

The program according to the embodiment includes a computer that captures a frame image including an image of an object captured by the image capturing unit, an image of the object captured by the image capturing unit, and a reference for each registered product registered in the dictionary. A function for executing a recognition process for extracting candidates for the registered product corresponding to the imaged object based on a degree of similarity indicating how similar the image is, and the capturing unit Detecting a change in the color attribute of the captured frame image and, when the color attribute exceeds a predetermined reference value, activates the means for executing the recognition process, and after the predetermined time has elapsed, the color attribute If there is no change, the recognition process is not executed .

FIG. 1 is a perspective view illustrating an example of a checkout system (store system) according to the embodiment. FIG. 2 is a block diagram illustrating a hardware configuration of the POS terminal and the commodity reading apparatus. FIG. 3 is a conceptual diagram illustrating the data structure of a PLU file. FIG. 4 is a block diagram illustrating functional configurations of the POS terminal and the commodity reading apparatus. FIG. 5 is a diagram illustrating an example of a frame image captured by the image capturing unit. FIG. 6 is a diagram illustrating an example of the confirmation screen. FIG. 7 is a diagram illustrating an example of a confirmation screen. FIG. 8 is a diagram illustrating an example of a screen on which illustration images of product candidates are displayed. FIG. 9 is a flowchart illustrating a procedure of product identification processing executed by the product reading device. FIG. 10 is a flowchart showing a procedure of sales registration processing executed by the POS terminal. FIG. 11 is an external perspective view showing the configuration of the self-POS. FIG. 12 is a block diagram showing a hardware configuration of the self-POS.

  Hereinafter, an information processing apparatus, a store system, and a program according to the present embodiment will be described with reference to the drawings, taking a checkout system as an example. The store system is a checkout system (POS system) provided with a POS terminal that performs registration and settlement of commodities related to one transaction. This embodiment is an application example to a checkout system introduced in a store such as a supermarket.

  FIG. 1 is a perspective view showing an example of a checkout system 1. As shown in FIG. 1, the checkout system 1 includes a product reading device 101 that reads information about a product, and a POS terminal 11 that performs registration and settlement of the product related to one transaction. Below, the example which applies the goods reading apparatus 101 as an information processing apparatus concerning this embodiment is demonstrated.

  The POS terminal 11 is placed on the upper surface of the drawer 21 on the checkout table 41. The drawer 21 is controlled by the POS terminal 11 for the opening operation. On the upper surface of the POS terminal 11, a keyboard 22 that is pressed down by an operator (a store clerk) is arranged. A display device 23 that displays information toward the operator is provided behind the keyboard 22 when viewed from the operator who operates the keyboard 22. The display device 23 displays information on the display surface 23a. A touch panel 26 is laminated on the display surface 23a. A customer display device 24 is erected so as to be rotatable further back than the display device 23. The customer display device 24 displays information on the display surface 24a. The customer display device 24 shown in FIG. 1 has the display surface 24a facing the front side in FIG. 1, but the customer display device 24 is rotated so that the display surface 24a faces the back side in FIG. Thus, the customer display device 24 displays information to the customer.

  A horizontally long table-shaped counter table 151 is arranged so as to form an L shape with the checkout table 41 on which the POS terminal 11 is placed. A load receiving surface 152 is formed on the upper surface of the counter table 151. A shopping basket 153 for storing the product G is placed on the cargo receiving surface 152. The shopping basket 153 may be divided into a first shopping basket 153a brought in by a customer and a second shopping basket 153b placed at a position sandwiching the commodity reading device 101 from the first shopping basket 153a. it can. The shopping basket 153 is not limited to a so-called basket shape, and may be a tray or the like. The shopping basket 153 (second shopping basket 153b) is not limited to a so-called basket shape, and may be a box shape, a bag shape, or the like.

  On the receiving surface 152 of the counter stand 151, the commodity reading apparatus 101 connected to the POS terminal 11 so as to be able to transmit and receive data is installed. The commodity reading apparatus 101 includes a thin rectangular housing 102. A reading window 103 is disposed in front of the housing 102. A display / operation unit 104 is attached to the upper portion of the housing 102. The display / operation unit 104 is provided with a display device 106 on which a touch panel 105 is laminated. A keyboard 107 is disposed on the right side of the display device 106. A card reading groove 108 of a card reader (not shown) is provided on the right side of the keyboard 107. A customer display device 109 for providing information to the customer is installed on the back left side of the display / operation unit 104 as viewed from the operator.

  Such a product reading apparatus 101 includes a product reading unit 110 (see FIG. 2). The merchandise reading unit 110 has an imaging unit 164 (see FIG. 2) disposed behind the reading window 103.

  In the first shopping basket 153a brought in by the customer, a product G related to one transaction is stored. The commodity G in the first shopping basket 153a is moved to the second shopping basket 153b by an operator who operates the commodity reading apparatus 101. In this movement process, the product G is directed to the reading window 103 of the product reading apparatus 101. At this time, the imaging unit 164 (see FIG. 2) arranged in the reading window 103 images the product G.

  The merchandise reading apparatus 101 displays a screen for designating which merchandise G included in the image captured by the imaging unit 164 corresponds to which merchandise registered in a PLU file F1 (see FIG. 3) described later. Displayed on the operation unit 104 and notifies the POS terminal 11 of the product ID of the specified product. In the POS terminal 11, based on the product ID notified from the product reading device 101, information related to sales registration such as the product classification, product name, and unit price of the product corresponding to the product ID is stored in a sales master file (not shown) or the like. And record sales.

  FIG. 2 is a block diagram illustrating a hardware configuration of the POS terminal 11 and the commodity reading apparatus 101. The POS terminal 11 includes a microcomputer 60 as an information processing unit that executes information processing. The microcomputer 60 is configured by connecting a ROM (Read Only Memory) 62 and a RAM (Random Access Memory) 63 to a CPU (Central Processing Unit) 61 that executes various arithmetic processes and controls each unit.

  The drawer 61, the keyboard 22, the display device 23, the touch panel 26, and the customer display device 24 are all connected to the CPU 61 of the POS terminal 11 through various input / output circuits (all not shown). . These are controlled by the CPU 61.

  The keyboard 22 includes a numeric key 22d, a temporary fastening key 22e, and a fastening key 22f on which numbers such as “1”, “2”, “3”... Including.

  An HDD (Hard Disk Drive) 64 is connected to the CPU 61 of the POS terminal 11. The HDD 64 stores programs and various files. All or a part of the programs and various files stored in the HDD 64 are copied to the RAM 63 and executed by the CPU 61 when the POS terminal 11 is activated. An example of a program stored in the HDD 64 is a product sales data processing program PR. An example of a file stored in the HDD 64 is a PLU file F1 distributed and stored from the store computer SC.

  The PLU file F1 is a product file in which an association between information related to sales registration of the product G and an image of the product G is set for each product G to be displayed and sold in the store.

  FIG. 3 is a conceptual diagram illustrating the data configuration of the PLU file F1. As shown in FIG. 3, the PLU file F1 includes, for each product G, a product ID uniquely assigned to the product, information on the product such as a product classification to which the product G belongs, a product name, a unit price, and a product image obtained by capturing the product This is a file for storing (reference image) and an illustration image showing the product as product information of the product G. The product image is a captured image (photograph) of the product used for determining the similarity. The PLU file F1 is configured to be readable by the commodity reading apparatus 101 via a connection interface 65 described later.

  Note that the data configuration of the PLU file F1 is not limited to the example of FIG. 3, and for example, feature quantities such as color and surface irregularities read from a product image may be stored for each product.

  Returning to FIG. 2, a communication interface 25 for executing data communication with the store computer SC is connected to the CPU 61 of the POS terminal 11 via an input / output circuit (not shown). The store computer SC is installed in a store backyard or the like. A PLU file F1 distributed to the POS terminal 11 is stored in the HDD (not shown) of the store computer SC.

  Further, the CPU 61 of the POS terminal 11 is connected to a connection interface 65 that enables data transmission / reception with the commodity reading apparatus 101. The product reading apparatus 101 is connected to the connection interface 65. The CPU 61 of the POS terminal 11 is connected to a printer 66 that prints on receipts. The POS terminal 11 prints the transaction content of one transaction on the receipt under the control of the CPU 61.

  The commodity reading apparatus 101 also includes a microcomputer 160. The microcomputer 160 is configured by connecting a ROM 162, a RAM 163, and a timer T to a CPU 161 via a bus. The ROM 162 stores a program executed by the CPU 161. The CPU 161 is connected to an imaging unit 164 and an audio output unit 165 via various input / output circuits (none of which are shown). The operations of the imaging unit 164 and the audio output unit 165 are controlled by the CPU 161. The display / operation unit 104 is connected to the product reading unit 110 and the POS terminal 11 via the connection interface 176. The operation of the display / operation unit 104 is controlled by the CPU 161 of the product reading unit 110 and the CPU 61 of the POS terminal 11.

  The imaging unit 164 includes an image sensor (not shown) such as a color CCD image sensor or a color CMOS image sensor, and a light source (not shown) such as an LED, and is controlled from the reading window 103 under the control of the CPU 161. It is an imaging means for performing imaging. For example, the imaging unit 164 captures a 30 fps moving image. Frame images (captured images) sequentially captured at a predetermined frame rate by the imaging unit 164 are stored in the RAM 163.

  In this embodiment, although details will be described later, imaging is performed to detect the product G directed to the reading window 103 for sales registration from the difference between the background frame image and the frame image including the product G. The imaging direction of the unit 164 is preferably a direction with little change in the background (for example, upward or downward).

  The audio output unit 165 is an audio circuit and a speaker for generating a preset warning sound or the like. The audio output unit 165 performs warning sound or audio notification under the control of the CPU 161.

  Furthermore, a connection interface 175 that connects to the connection interface 65 of the POS terminal 11 and enables data transmission / reception with the POS terminal 11 is connected to the CPU 161. In addition, the CPU 161 transmits and receives data to and from the display / operation unit 104 via the connection interface 175.

  Next, functional configurations of the CPU 161 and the CPU 61 that are realized by the CPU 161 and the CPU 61 executing programs will be described with reference to FIG.

  FIG. 4 is a block diagram illustrating functional configurations of the POS terminal 11 and the commodity reading apparatus 101. As illustrated in FIG. 4, the CPU 161 of the commodity reading device 101 executes a program stored in the ROM 162, thereby executing an image capturing unit 51 that is a capturing unit, a commodity detecting unit 52, and a similarity that is a similarity calculating unit. It has functions as a calculation unit 53, a similarity determination unit 54 that is a product candidate extraction unit, a confirmation notification unit 55, a product candidate presentation unit 56, an input reception unit 57, and an information output unit 58. Similarly, the CPU 61 of the POS terminal 11 has a function as the sales registration unit 611 by executing the program PR.

  The image capturing unit 51 outputs an imaging on signal to the imaging unit 164 and causes the imaging unit 164 to start an imaging operation. The image capturing unit 51 sequentially captures frame images captured by the image capturing unit 164 and stored in the RAM 163 after the start of the image capturing operation. The capturing of the frame image by the image capturing unit 51 is performed in the order stored in the RAM 163.

  FIG. 5 is a diagram illustrating an example of a frame image captured by the image capturing unit 51. As shown in FIG. 5, when the operator holds the product G over the reading window 103, all or part of the product G is photographed in the reading region R of the imaging unit 164.

  By the way, when the product G (object) is not located near the light source of the imaging unit 164, that is, near the reading window 103, the photographed image by the imaging unit 164 is in a state where the brightness is 0 or close thereto. Then, when the product G (object) to be recognized is brought close to the reading window 103, the light from the light source is reflected on the product G (object), so that the brightness of the image captured by the imaging unit 164 changes brightly.

  The image capturing unit 51 detects such brightness change (change in color attribute), and performs object recognition processing (product detection unit 52, product detection unit 52, when the brightness exceeds a predetermined reference value). The similarity calculation unit 53, the similarity determination unit 54, the confirmation notification unit 55, the product candidate presentation unit 56, and the input reception unit 57) are activated. Thereby, it is possible to suppress the CPU load when the object recognition process described later is unnecessary.

  Note that, depending on the installation environment of the product reading apparatus 101, there may be variations in the captured image in the absence of the product G (object). Therefore, an object recognition engine (product detection unit 52, similarity calculation unit 53, similarity determination unit 54, confirmation notification unit 55, so as not to increase the CPU load due to unnecessary object recognition processing due to the influence of unnecessary disturbances, It is necessary to control and set the lightness reference value for operating the commodity candidate presenting unit 56 and the input receiving unit 57).

  Note that as the color attribute, in addition to the lightness representing the brightness of the color, a saturation representing the intensity of the color may be used. Note that the object recognition engine (the product detection unit 52, the similarity calculation unit 53, the similarity determination unit 54, the confirmation notification unit 55, the product candidate presentation unit 56, and the input reception unit 57) is activated in a plurality of colors. Based on the attribute, it may be determined whether the reference value has been exceeded.

  The product detection unit 52 detects all or part of the product G included in the frame image captured by the image capture unit 51 using a pattern matching technique or the like. Specifically, a contour line or the like is extracted from an image obtained by binarizing the captured frame image. Next, based on the difference between the contour line extracted from the previous frame image and the contour line extracted from the current frame image, a product directed to the reading window 103 for sales registration is detected.

  The previous frame image is, for example, an object recognition engine (a product detection unit 52, a similarity calculation unit 53, a similarity determination unit 54, a confirmation notification unit 55, a product candidate presentation unit 56, and an input reception unit 57). This is the background frame image captured by the image capturing unit 51 before the image recognition process is started, that is, before the object recognition process is started. The automatic acquisition of the background frame image as the previous frame image before the activation of the object recognition application is performed in an environment where the background is relatively unchanged (for example, the imaging unit 164 receives the load on the upper surface of the counter table 151). This is useful for use in a case where the vertical downward direction is attached to the surface 152 as the reading direction. The environment includes the state of lighting (the surroundings and lighting of the commodity reading apparatus 101 itself), the clothes of the user, and the like.

  Further, as a previous frame image, a background frame image captured by the image capturing unit 51 immediately after execution of the previous object recognition process may be used. This is useful for use in environments where the background is relatively changeable, or where the customer's clothes and distance from the product reading device 101 are expected to change variously, such as self-checkout. It is.

  Furthermore, the user may acquire the previous frame image as a background at an arbitrary timing. There are various cases in which the previous frame image is acquired as a background at an arbitrary timing, but this is effective when, for example, the PLU file F1, which is a dictionary, is created.

  As another method for detecting a product, the presence or absence of a skin color region is detected from a captured frame image. Next, when a skin color area is detected, that is, when a clerk's hand is detected, it is assumed that the clerk's hand is grasped by detecting the above-described contour line in the vicinity of the skin color area. Try to extract the outline of the product. At this time, when the contour indicating the shape of the hand and the contour of the other object are detected in the vicinity of the contour of the hand, the product is detected from the contour of the object.

  The similarity calculation unit 53 reads the surface state such as the hue of the product G and the unevenness of the surface as a feature amount from all or a part of the product G imaged by the imaging unit 164. The similarity calculation unit 53 does not consider the outline or size of the product G in order to shorten the processing time.

  In addition, the similarity calculation unit 53 reads the surface state such as the color of the registered product and the unevenness of the surface from the product image of each product (hereinafter referred to as registered product) registered in the PLU file F1 as a feature amount. The similarity between the product G and the product registered in the PLU file F1 is calculated by comparing with the feature amount of the product G. Here, the similarity is the degree of similarity of all or part of the product G when the product image of each product stored in the PLU file F1 is 100% = “similarity: 1.0”. It shows whether you are doing. Note that, for example, the similarity may be calculated by changing the weight between the color tone and the surface roughness.

Recognizing an object contained in an image in this way is called generic object recognition. Regarding such general object recognition, various recognition techniques are described in the following documents.
Keiji Yanai, “Current Status and Future of General Object Recognition”, IPSJ Journal, Vol. 48, no. SIG16 [Search August 10, 2010], Internet <URL: http://mm.cs.uec.ac.jp/IPSJ-TCVIM-Yanai.pdf>

Further, techniques for performing general object recognition by dividing an image into regions for each object are described in the following documents.
Jamie Shotton et al., “Semantic Texton Forests for Image Categorization and Segmentation”, [searched August 10, 2010], Internet <URL: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1. 1.145.3036 & rep = rep1 & type = pdf>

  Note that the method of calculating the similarity between the captured image of the product G and the product image of the registered product registered in the PLU file F1 is not particularly limited. For example, the similarity between the captured image of the product G and each registered product registered in the PLU file F1 may be calculated as an absolute evaluation or may be calculated as a relative evaluation.

  When calculating the similarity as an absolute evaluation, the captured image of the product G and each registered product registered in the PLU file F1 are compared on a one-to-one basis, and the similarity derived as a result of this comparison is used as it is. do it. Further, when calculating the similarity as a relative evaluation, if five registered products (products GA, GB, GC, GD, GE) are registered in the PLU file F1, the captured product G is The similarity is 0.6, the similarity is 0.1 for the product GB, the similarity is 0.1 for the product GC, the similarity is 0.1 for the product GD, and the product GE On the other hand, the similarity may be calculated such that the similarity is 0.1, and the total similarity with each registered product is 1.0 (100%).

  The similarity determination unit 54 compares the similarity between the image of the product G and the product image registered in the PLU file F1 for each frame image captured by the image capturing unit 51. In the present embodiment, a plurality of conditions for the similarity between the product image of the registered product and the image of the product G are provided in stages, and the similarity determination unit 54 determines the registered product according to the satisfied condition or Select product candidates. Although the conditions regarding the degree of similarity are not particularly limited, a case where conditions a to c are used will be described below.

  Here, the condition a and the condition b are the first conditions according to the present embodiment, and the product G captured by the imaging unit 164 is determined as one product among the registered products registered in the PLU file F1. It is a condition. The condition c is a second condition according to the present embodiment, and is a condition for extracting a candidate for the product G imaged by the imaging unit 164 from the registered products registered in the PLU file F1.

  The similarity determination unit 54 determines (determines) a registered product that satisfies the condition a or the condition b as a product that corresponds to the product G captured by the imaging unit 164 on a one-to-one basis (hereinafter referred to as a confirmed product). Further, the similarity determination unit 54 determines that the registered product satisfying the condition c is not a confirmed product but a candidate for the product G imaged by the imaging unit 164 (hereinafter referred to as a product candidate). Then, product candidates for the product G are extracted by extracting registered products satisfying the condition c from the plurality of registered products registered in the PLU file F1.

  The details of the conditions a to c are not particularly limited as long as the conditions a to c are set stepwise according to the degree of similarity, but as an example, the conditions a to c can be provided by a plurality of preset threshold values. Here, the case where the conditions a to c are set by the first threshold value to the third threshold value will be described. Note that the magnitude relationship between the first to third thresholds is first threshold> second threshold> third threshold.

  The similarity determination unit 54 counts the number of times that the degree of similarity with the registered product is equal to or higher than a predetermined first threshold (for example, 90%), and the condition a is satisfied when the number of times exceeds a predetermined number. It is determined that When the first threshold is set sufficiently high so that no erroneous determination is made, the condition a may be determined by setting the predetermined number of times as one.

  The similarity determination unit 54 determines that the condition b is satisfied when the similarity to the registered product is less than the first threshold (for example, 90%) and equal to or greater than the second threshold (for example, 75%) that is smaller than the first threshold. Determined to be satisfied. Then, it is determined that the registered product that satisfies the condition b is a confirmed product, but requires a confirmation operation by the operator. Note that the number of times the similarity with the registered product is less than the first threshold (for example, 90%) and the second threshold value (for example, 75%) is less than the first threshold is counted, It may be determined that the condition b is satisfied.

  Furthermore, when the similarity with the registered product is less than the second threshold (for example, 75%) and greater than or equal to the third threshold (for example, 10%) smaller than the second threshold, the similarity determination unit 54 determines that the condition c is Determined to be satisfied. Furthermore, the number of times that the degree of similarity with the registered product is less than the second threshold value (for example, 75%) and the third threshold value (for example, 10%) that is less than the second threshold value is counted. You may determine with the condition c being satisfied when it becomes above.

  Each condition a to c can be appropriately set according to the degree of similarity, the number of determinations, and the like, and is not limited to the above-described example. Moreover, the predetermined number of times used for the determination of the conditions a to c may be different for each condition.

  The confirmation notification unit 55 notifies the operator or customer that the product imaged by the imaging unit 164 is uniquely confirmed as a registered product satisfying the condition a or the condition b by image output or voice output. To do.

  More specifically, the confirmation notification unit 55 confirms that the registered product satisfying the condition a is uniquely confirmed as the product (confirmed product) captured by the imaging unit 164 (see FIG. 6). Is displayed on the display device 106.

  FIG. 6 is a diagram illustrating an example of the confirmation screen 71. When there is a registered product that satisfies the condition a, the confirmation notification unit 55 stops displaying the captured image in the reading region R (see FIG. 5), and displays the illustration image G1 corresponding to the confirmed product and the product name “carrot” in the PLU. The data is read from the file F1 and displayed on the confirmation screen 71. Further, the confirmation notification unit 55 displays the product name and product price (unit price) of the confirmed product read from the PLU file F1 in the product name display area 81 and the price display area 82, respectively. The confirmation notification unit 55 may display a product image (photo) read from the PLU file F1 instead of the illustration image G1.

  Further, the confirmation notifying unit 55 sounds a voice equivalent to the conventional barcode reading, assuming that the object recognition is confirmed with sufficient reliability in accordance with the display timing of the confirmation screen 71. Informs that the recognition is completed normally and the data is confirmed.

  Further, the confirmation notification unit 55 outputs information related to the confirmed product such as the product name read from the PLU file F1 to the audio output unit 165 in accordance with the display timing of the confirmation screen 71. The voice output unit 165 notifies the operator or customer of information indicating the confirmed product by outputting the input information.

  Further, the confirmation notification unit 55 displays a confirmation screen 72 (see FIG. 7) for receiving a final confirmation operation as to whether or not the registered product (confirmed product) satisfying the condition b is the product G imaged by the imaging unit 164. It is displayed on the display device 106.

  FIG. 7 is a diagram illustrating an example of the confirmation screen 72. When there is a registered product satisfying the condition b, the confirmation notification unit 55 reads the illustration image G1 corresponding to the confirmed product from the PLU file F1 and displays it on the confirmation screen 72. Further, the confirmation notification unit 55 uses a product name of the confirmed product read from the PLU file F1, and a message asking whether or not the read product G is a product of the illustration image G1 is “carrot?” Or the like. Is displayed. Further, the confirmation screen 72 is provided with buttons such as “Yes / No” so as to be selectable by a touch operation on the touch panel 105.

  As described above, on the confirmation screen 72, as a result of the similarity determination, the product name and product image of the registered product (confirmed product) that is uniquely selected for one product G are shown. Are displayed in a one-to-one relationship. Therefore, the confirmation screen 72 is a screen for notifying that the registered product satisfying the condition b is uniquely determined as the product G imaged by the imaging unit 164.

  In this embodiment, when the product imaged in this way is uniquely determined, an illustration image of the confirmed product is displayed instead of the captured image. Accordingly, the operator can intuitively recognize that the identification of the product has been confirmed, and can recognize at a glance which product the identified product is.

  Note that the confirmation notification unit 55 may cause the audio output unit 165 to output the information regarding the confirmed product and the information for prompting confirmation in synchronization with the timing at which the confirmation screen 72 is displayed. You may not do it. The presence or absence of audio output on the confirmation screen 71 and the confirmation screen 72 can be set as appropriate.

  The product candidate presentation unit 56 causes the display device 106 to display information on the registered product that satisfies the condition c as a product candidate. More specifically, the product candidate presentation unit 56 reads the illustration image and product name of the registered product satisfying the condition c from the PLU file F1, and uses the display device 106 from the one with the high similarity calculated by the similarity calculation unit 53. Are output sequentially. The display device 106 displays the product candidate illustration images and product names in descending order of similarity in the product candidate presentation area 83 (see FIG. 8).

  FIG. 8 is a diagram illustrating an example of a screen on which illustration images G1, G2, and G3 of product candidates are displayed. As illustrated in FIG. 8, product candidate illustration images G1, G2, and G3 and product names are displayed in the product candidate presentation area 83 in order from registered products with a high degree of similarity. These illustration images G1, G2, and G3 are configured to be selectable in accordance with a selection operation on the touch panel 105. A selection button 84 for selecting a product from the product list is provided below the product candidate presentation area 83, and the product selected from the product list is processed as the above-described confirmed product. Although FIG. 8 shows an example in which three product candidates corresponding to the illustration images G1 to G3 are displayed, the number of product candidates and the display method are not particularly limited. In addition, a product image (photo) may be displayed instead of the illustration image.

  Further, the product candidate presentation unit 56 may cause the audio output unit 165 to output a voice to the effect that there are a plurality of candidates at the timing when the product candidate presentation region 83 is displayed. Audio output may not be performed at the timing when 83 is displayed.

  Further, the product candidate presentation unit 56 may cause the audio output unit 165 to output information that can easily determine the distinction between vegetables and fruits. Furthermore, the product candidate presentation unit 56 selects the selection button 84 when, for example, the product displayed in the product candidate presentation area 83 is a highly similar product (such as a variety in the same category or a similar green vegetable). Information such as the presence or the automatic narrowing may be output to the audio output unit 165.

  Even if the product candidate illustration images G <b> 1 to G <b> 3 are displayed on the display device 106, when the selection operation for these product candidates is not accepted, the image capturing process by the image capturing unit 51, the product detecting unit 52 The detection process and the similarity calculation process by the similarity calculation unit 53 are continued. Therefore, while the product candidate is not selected, the captured image of the reading region R is displayed on the screen of the display device 106.

  The input receiving unit 57 receives various input operations corresponding to the display on the display device 106 via the touch panel 105 or the keyboard 107. For example, the input receiving unit 57 receives an input operation (confirmation operation) indicating that the product of the displayed illustration image G1 is finally confirmed based on a selection operation on the confirmation screen 72 (see FIG. 7). . Note that the confirmation notification unit 55 displays the above-described confirmation screen 71 on the display device 106 when the input reception unit 57 receives the confirmation operation.

  The input receiving unit 57 receives a selection operation for any one of the illustration images G1 to G3 (see FIG. 8) of the product candidates displayed on the display device 106. The input receiving unit 57 receives the registered product of the selected illustration image as a confirmed product for the product G. When the product detection unit 52 can detect a plurality of products G, the input receiving unit 57 may receive a selection operation of a plurality of product candidates from the product candidates. When the input receiving unit 57 accepts the selection operation, the confirmation notifying unit 55 causes the display device 106 to display a confirmation screen 71 that displays the accepted product candidate as a confirmed product.

  The information output unit 58 outputs information indicating the product (for example, product ID, product name, etc.) to the POS terminal 11 via the connection interface 175 for the confirmed product confirmed as described above.

  Note that the information output unit 58 may output the sales quantity separately input via the touch panel 105 or the keyboard 107 to the POS terminal 11 together with the product ID and the like. Further, as information output from the information output unit 58 to the POS terminal 11, the product ID read by the information output unit 58 from the PLU file F1 may be directly notified, or a product name that can specify the product ID. Alternatively, the file names of product images and illustration images may be notified, and the storage location of the product ID (storage address in the PLU file F1) may be notified to the POS terminal 11.

  The sales registration unit 611 of the POS terminal 11 performs sales registration of the corresponding product based on the product ID and the sales quantity output from the information output unit 58. Specifically, the sales registration unit 611 refers to the PLU file F1, and records the notified product ID and the product classification, product name, unit price, etc. corresponding to the product ID together with the number of sales in a sales master file or the like. To register sales.

  The product reading apparatus 101 also includes a known code symbol reading unit (not shown) that optically reads a code symbol such as a barcode or a two-dimensional code as information about the product. The merchandise reading apparatus 101 transmits a merchandise ID, which is a number obtained by reading the code symbol by the code symbol reading section, to the POS terminal 11. The product reading apparatus 101 includes an object recognition processing mode that reads information about a product by object recognition processing by the product reading unit 110 as described above, and a code symbol reading mode that reads information about a product by code symbol reading processing by a code symbol reading unit. Can be switched by a key operation of the keyboard 107 or the like.

  The operation of the checkout system 1 when the commodity reading apparatus 101 is set to the code symbol reading mode will be briefly described. When the product reading apparatus 101 is set to the code symbol reading mode, the POS terminal 11 determines that the number obtained by reading the code symbol in the code symbol reading unit matches the product ID stored in the PLU file F1. Then, a signal indicating that and information related to sales registration such as the product classification, product name, and unit price of the product corresponding to the product ID are transmitted to the product reading apparatus 101. On the other hand, when the product reading apparatus 101 receives a signal indicating that it matches the product ID and information related to sales registration of the product corresponding to the product ID, for example, the product reading device 101 emits a beeping sound due to a short buzzer sound. At the same time, information related to sales registration is displayed on the display device 106.

  Based on the product ID notified from the product reading device 101, the POS terminal 11 acquires information related to sales registration such as product classification, product name, unit price, etc. of the product corresponding to the product ID from the PLU file F1, and stores the sales master. Record sales in a file (not shown) and register sales.

  Next, the operation of the checkout system 1 in the object recognition processing mode will be described in detail. First, the operation of the commodity reading apparatus 101 will be described. FIG. 9 is a flowchart illustrating a procedure of product identification processing executed by the product reading apparatus 101. In FIG. 9, the first threshold is set to 90% (0.90) similarity, the second threshold is set to 75% (0.75), and the third threshold is set to 10% (0.10) similarity. Although described, each threshold value is not limited to these.

  When processing is started in response to the start of product registration by the POS terminal 11, the image capturing unit 51 outputs an imaging on signal to the imaging unit 164 and starts imaging by the imaging unit 164 (step S11). The image capturing unit 164 captures the background image data captured and stored in the RAM 163 (step S12).

  As described above, before starting the object recognition engine (the product detection unit 52, the similarity calculation unit 53, the similarity determination unit 54, the confirmation notification unit 55, the product candidate presentation unit 56, the input reception unit 57), the background frame image By acquiring the above, it is possible to acquire the background including the current state of illumination (the illumination of the surroundings and the product reading apparatus 101 itself), the clothes of the user, and the like.

  Next, the image capturing unit 51 captures a frame image (captured image) captured by the image capturing unit 164 and stored in the RAM 163 (step S13), and starts timing by the timer T (step S14).

  Next, the image capturing unit 51 acquires the color attribute (for example, brightness) of the frame image captured by the image capturing unit 51 (step S15), and the color attribute is changed within a predetermined time (step S16). : No), if the color attribute (for example, lightness) exceeds a predetermined reference value (step S17: Yes), it is determined that the product G is directed to the reading window 103 for sales registration, and the timer T (Step S18), the object recognition engine (product detection unit 52, similarity calculation unit 53, similarity determination unit 54, confirmation notification unit 55, product candidate presentation unit 56, input acceptance) Unit 57) is activated (step S19), and the process proceeds to step S20.

  On the other hand, when there is no change in the color attribute within a predetermined time (step S16: No), for example, the product G is left in front of the product reading apparatus 101, and the color attribute (for example, brightness) Therefore, the reference value of the color attribute (for example, brightness) is changed (step S21). That is, if the reference value is set to be equal to or higher than the current brightness after a predetermined time has elapsed (for example, after 2 seconds), the recognition process for the product G that has been left is not executed. When the reference value is changed in this way, it may be returned to the original reference value by using a change in brightness as a result of imaging the next object.

  If the color attribute (for example, brightness) does not exceed the predetermined reference value (step S17: No), the process returns to step S13, and the next frame image (captured image) is captured.

  Next, the product detection unit 52 detects all or part of the product G from the frame image captured by the image capture unit 51 based on the difference between the background frame image and the frame image captured by the image capture unit 51. (Step S20).

  Subsequently, the similarity calculation unit 53 reads the feature amount of the product G from all or part of the image of the product G, and compares it with the feature amount of each product image registered in the PLU file F1 to determine whether the product is registered. The similarity is calculated (step S22).

  The similarity determination unit 54 determines whether there is a registered product with a similarity of 90% or more (step S23). If there is no registered product that is 90% or more (step S23: No), the process proceeds to step S25. If there is a registered product that is 90% or more (step S23: Yes), it is determined whether or not the number of times that the similarity to the same registered product is 90% or more has reached a predetermined number (for example, 3 times). (Step S24). When the predetermined number is not reached (step S24: No), the process returns to step S12, and the image capturing unit 51 captures a new frame image captured by the image capturing unit 164.

  When the predetermined number of times has been reached (step S24: Yes), the confirmation notification unit 55 displays a confirmation screen 71 (see FIG. 6) including an illustration image of the confirmed product, and first indicates that the product has been confirmed. By confirming the voice and the product name of the confirmed product by voice, the confirmed product is notified (step S31). The first sound is a sound similar to a notification sound indicating that the product ID coincides with the product ID “beep” generated by, for example, a short buzzer sound when the product reading apparatus 101 is set to the code symbol reading mode. In this way, by making the sound similar to the notification sound indicating that it matches the product ID in the code symbol reading mode, it is easy to understand that it has been determined from the long-standing practice. Even if only the object recognition processing mode is not provided without the code symbol reading mode, the first sound is, for example, “beep” when the product reading apparatus 101 is set to the code symbol reading mode. It is better to use a sound similar to a notification sound indicating that the product ID matches.

  Further, the information output unit 58 outputs the product ID of the registered product determined as the confirmed product to the POS terminal 11 together with the number of sales separately input via the keyboard 107 (step S32), and thereafter the process of step S33. Migrate to

  Step S23: In the case of No, the similarity determination unit 54 determines whether there is a registered product whose similarity is 75% or more and less than 90% (step S25). If there is a registered product whose similarity is within this range (step S25: Yes), it is determined that the registered product is a confirmed product that requires operator confirmation, and a confirmation screen 72 is displayed on the display device 106. Then, the information about the product and the information for prompting confirmation are notified by voice (step S26). The input receiving unit 57 determines whether or not “Yes” is selected on the confirmation screen 72 (see FIG. 7) (step S27). When “Yes” is selected (step S27: Yes), the process proceeds to step S31, and the confirmation notification unit 55 displays a confirmation screen 71 and notifies the product name of the confirmed product by voice. On the other hand, when “No” is selected (step S27: No), the process returns to step S12.

  On the other hand, when there is no registered product whose similarity is 75% or more and less than 90% (step S25: No), the similarity determination unit 54 determines whether there is a registered product whose similarity is 10% or more and less than 75%. And the registered products whose similarity is within this range are extracted as product candidates for the product G (step S28). If there is no registered product within this range (step S28: No), the process returns to step S12. When there is a registered product with a similarity of 10% or more and less than 75% (step S28: Yes), the similarity determination unit 54 determines that the corresponding registered product is a product candidate for the product G. Then, the product candidate presenting unit 56 sorts the illustration images and product names of the registered products determined as the product candidates in descending order of similarity and displays them in the product candidate presentation area 83, and indicates that there are a plurality of candidates. Voice notification is made with the second voice (step S29). The second sound is a sound different from the first sound described above, and is, for example, a “buzzy” sound due to the sound of a slightly long buzzer sound or a sound prompting selection.

  In addition, when there are a plurality of candidates, the product candidate presentation unit 56 may notify a sound that can easily distinguish between vegetables and fruits, varieties in the same category, similar vegetables, and the like. . For example, in the case of highly similar products (such as green vegetables and apple varieties), the selection can be narrowed down.

  The input receiving unit 57 determines whether a selection operation for the product image of the registered product has been received (step S30). When the selection is accepted (step S30: Yes), the process proceeds to step S31, and the confirmation notification unit 55 displays the confirmation screen 71. On the other hand, when selection is not accepted (step S30: No), it transfers to step S12.

  In step S <b> 33, the CPU 161 determines the presence / absence of business end from the POS terminal 11 based on the end notification of the product registration. When the business is continued (step S33: No), the CPU 161 returns the process to step S12, and the image capture unit 51 captures the background image data captured by the image capture unit 164 and stored in the RAM 163 and continues the process. Let As described above, by using the frame image of the background captured by the image capturing unit 51 immediately after the previous object recognition processing is performed, the background of the background is relatively easy to change, or the customer's Even in the case where it is predicted that the clothes, the distance from the product reading apparatus 101, and the like will be changed variously, it is possible to reliably detect all or part of the product G.

  When the work is to be ended (step S33: Yes), the image capturing unit 51 outputs an imaging off signal to the imaging unit 164, ends the imaging by the imaging unit 164 (step S34), and ends the process.

  Next, the operation of the POS terminal 11 will be described. FIG. 10 is a flowchart showing a procedure of sales registration processing executed by the POS terminal 11.

  First, when processing is started in response to the start of product registration in response to an operation instruction on the keyboard 22, the CPU 61 determines the product ID of the confirmed product and the number of items sold, which is output by the product reading device 101 in step S32 of FIG. Is received (step S41). Next, the sales registration unit 611 reads the product type, unit price, and the like from the PLU file F1 based on the product ID and the sales quantity received in step S41, and stores the sales of the product G read by the product reading device 101 as a sales master file. (Step S42). Subsequently, the CPU 61 determines whether or not there is an end of business due to the end of sales registration or the like by an operation instruction of the keyboard 22 (step S43). When the business is continued (step S43: No), the CPU 61 returns to step S41 again and continues the process. When the business is to be ended (step S43: Yes), the CPU 61 ends the process.

  As described above, according to the present embodiment, the image capturing unit 51 that captures a frame image including the image of the product G captured by the imaging unit 164 detects a change in the color attribute of the captured frame image, When the color attribute exceeds a predetermined reference value, the object recognition engine (product detection unit 52, similarity calculation unit 53, similarity determination unit 54, confirmation notification unit 55, product candidate presentation unit 56, input reception unit) 57) is activated. Therefore, the CPU load when the object recognition process is unnecessary can be suppressed.

  As mentioned above, although embodiment of this invention was described, the said embodiment was shown as an example and is not intending limiting the range of invention. The above embodiment can be implemented in various other forms, and various omissions, replacements, changes, additions, and the like can be made without departing from the scope of the invention. Moreover, the said embodiment and its deformation | transformation are included in the range of the invention, the summary, and the invention described in the claim, and its equal range.

  For example, in the above-described embodiment, the product reading apparatus 101 captures one product G at a time. However, the number of products G captured at a time is not particularly limited, and may be plural. When imaging a plurality of products G at a time, the similarity between the plurality of products G and the images (G1, G2, G3,...) Of the registered products is calculated, By comparing these, the confirmed product and the candidate product may be selected.

  Further, the configuration of each display screen described above is not limited to the examples of FIGS. 5 to 8, and a display area and operation buttons for displaying other elements may be provided.

  In the above embodiment, the POS terminal 11 includes the PLU file F1. However, the present invention is not limited thereto, and the product reading apparatus 101 may include the PLU file F1, or the POS terminal 11 and the product reading apparatus 101. The external device that can be accessed may be provided with the PLU file F1.

  In the above embodiment, the product reading apparatus 101 has the functions of the similarity calculation unit 53 and the similarity determination unit 54. However, the present invention is not limited thereto, and the POS terminal 11 includes the similarity calculation unit 53, the similarity determination unit. It is good also as a form which provides the function of 54 and outputs a calculation result and a determination result to the goods reading apparatus 101. FIG.

  In the above description, the example in which the similarity is determined in four stages using the three threshold values of the first to third thresholds as the plurality of threshold values has been described. However, the embodiment is not limited thereto. It may be determined in more stages using three or more threshold values, or may be determined using two or less threshold values. Each threshold value may be provided so as to be changeable by the user. Moreover, although the example which made the 1st-3rd threshold value and conditions ac common to all goods was given in the above-mentioned, it is not limited to this, Even if each threshold value and conditions are set for every registered goods, respectively. Good.

  In the above description, the first condition is divided into two stages: the case where the confirmation screen 72 is displayed (condition b) and the case where the confirmation screen 72 is not displayed (condition a). One condition does not have to be divided into multiple stages. That is, when another example is shown along with the above-described example, the product may be determined without displaying the confirmation screen 72 when any of the conditions a and b is satisfied. It may be possible to set whether or not to display.

  Moreover, in the said embodiment, although the checkout system 1 comprised by the POS terminal 11 and the goods reading apparatus 101 was applied as a store system, it is not restricted to this, The function of the POS terminal 11 and the goods reading apparatus 101 is provided. Alternatively, the present invention may be applied to a single-unit apparatus. As a single device having the functions of the POS terminal 11 and the commodity reading device 101, there is a self-checkout device (hereinafter simply referred to as self-POS) installed and used in a store such as a supermarket.

  11 is an external perspective view showing the configuration of the self-POS 200, and FIG. 12 is a block diagram showing the hardware configuration of the self-POS 200. In addition, below, the same code | symbol is attached | subjected and shown about the same structure shown by FIG. 1 and FIG. 2, and the duplicate description is abbreviate | omitted. As shown in FIGS. 11 and 12, the main body 202 of the self-POS 200 includes a display device 106 having a touch panel 105 disposed on the surface thereof, and a product reading unit that reads product images for recognizing (detecting) product types and the like. 110 is provided.

  For example, a liquid crystal display is used as the display device 106. The display device 106 is a guidance screen for notifying the customer of the operation method of the self-POS 200, various input screens, a registration screen for displaying product information read by the product reading unit 110, a total price of goods, a deposit price, and change. Display the amount, etc. and display the payment screen for selecting the payment method.

  The product reading unit 110 reads a product image by the imaging unit 164 by a customer holding the code symbol attached to the product over the reading window 103 of the product reading unit 110.

  Further, on the right side of the main body 202, a product placement table 203 for placing unsettled products in a basket is provided, and on the left side of the main body 202, a product placement table 204 for placing settled products is provided. There are provided a bag hook 205 for hanging a bag for putting a product already settled, and a temporary placing table 206 for temporarily placing the settled product before putting it in the bag. The product placement tables 203 and 204 are provided with weighing machines 207 and 208, respectively, and have a function of confirming that the product weight is the same before and after settlement.

  In addition, the main body 202 of the self-POS 200 is provided with a changer 201 for depositing banknotes for payment and receiving fishing banknotes.

  When the self-POS 200 having such a configuration is applied to a store system, the self-POS 200 functions as an information processing apparatus.

  In addition, the program executed by each device of the above embodiment is provided by being incorporated in advance in a storage medium (ROM or storage unit) included in each device, but is not limited thereto, and can be installed in a form or executable. Various types of files may be recorded and provided on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disk). Furthermore, the storage medium is not limited to a medium independent of a computer or an embedded system, but also includes a storage medium in which a program transmitted via a LAN, the Internet, or the like is downloaded and stored or temporarily stored.

  Further, the program executed by each device of the above embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network, or via a network such as the Internet. It may be configured to be provided or distributed.

DESCRIPTION OF SYMBOLS 1 Store system 51 Acquisition means 53 Similarity calculation means 54 Goods candidate extraction means 101,200 Information processing apparatus 164 Imaging means 611 Sales registration processing means F1 Dictionary

JP 2003-173369 A

Claims (6)

Capture means for capturing a frame image including an image of the object imaged by the imaging means;
The registered product corresponding to the imaged object based on the similarity indicating how similar the image of the object imaged by the imaging means and the reference image of each registered product registered in the dictionary are Means for executing recognition processing for extracting candidates,
With
The capturing means detects a change in the color attribute of the captured frame image, and activates a means for executing the recognition process when the color attribute exceeds a predetermined reference value, and a predetermined time has elapsed. If the color attribute does not change later, the recognition process is not executed.
Information processing device. The color attribute for which the capturing means detects a change is lightness representing the brightness of the color.
The information processing apparatus according to claim 1. The color attribute that the capturing means detects a change is a saturation representing the strength of the color,
The information processing apparatus according to claim 1 or 2. The capturing means dynamically changes the reference value;
The information processing apparatus according to claim 1. Imaging means;
Capture means for capturing a frame image including an image of the object imaged by the imaging means;
The registered product corresponding to the imaged object based on the similarity indicating how similar the image of the object imaged by the imaging means and the reference image of each registered product registered in the dictionary are Means for executing recognition processing for extracting candidates,
Sales registration processing means for performing sales registration processing of the registered product when the registered product candidate is one, or one registered product selected when there are a plurality of registered product candidates;
With
The capturing means detects a change in the color attribute of the captured frame image, and activates a means for executing the recognition process when the color attribute exceeds a predetermined reference value, and a predetermined time has elapsed. If the color attribute does not change later, the recognition process is not executed.
Store system. Computer
Capture means for capturing a frame image including an image of the object imaged by the imaging means;
The registered product corresponding to the imaged object based on the similarity indicating how similar the image of the object imaged by the imaging means and the reference image of each registered product registered in the dictionary are Means for executing recognition processing for extracting candidates,
Function as
The capturing means detects a change in the color attribute of the captured frame image, and activates a means for executing the recognition process when the color attribute exceeds a predetermined reference value, and a predetermined time has elapsed. If the color attribute does not change later, the recognition process is not executed.
program.

Images