The present invention relates to detecting surface characteristics of food objects. More particularly, it relates to detecting defects on the surface of the food objects while the food objects are being transported on a conveyor.
Inspection systems for surface detection of e.g. blood spots or melanin spots on food objects are known wherein either a 2D imaging device or a 3D imaging device is used. A common problem with such surface detection is that false positives, i.e. wrong indications of defects present on the scanned surface, are relatively common. For example, a 2D scan of the surface may detect a colour difference over a certain region and it is uncertain judging from this data whether the indicated defect is a blood discolouration or a hole or a shadow or an indentation/recess.
The present invention aims to provide an apparatus and a method for detecting surface characteristics on incoming food objects that may be conveyed by a conveyor apparatus. The food objects may be of any suitable shape and type.
A first imaging device is provided for capturing two-dimensional image data (2D) pertaining to the food objects and a second imaging device for capturing three-dimensional image data (3D) of the food objects. At least one image processing unit is configured to utilize either one of the 2D or the 3D image data in determining whether a potential defect is present on the surface of the food object. The image processing unit may comprise a computer running image processing data software and having access to the image data stored in a computer memory. The image processing unit further determines a surface position of the potential defect, in case such a potential defect property is detected. To determine whether the potential defect is actually a defect and not a surface anomaly, such as a hole or recess, the image processing unit utilizes the remaining one of the 2D or the 3D image data in determining whether an actual defect is present on the surface of the incoming food object at the earlier determined surface position. An output unit may indicate whether an actual defect is present on the surface of the incoming food object at the determined surface position by outputting defect related data in case both of the 2D and the 3D image data indicate that is the case.
The first imaging device may be arranged to acquire the 2D image data before the second imaging device acquires the 3D image data. The first imaging device may as an example comprise any type of a digital camera that captures 2D surface image of the food objects, and the second imaging device may e.g. comprise a line scanner comprising a laser source that emits a 2D laser line on the surface and where a camera detects the reflected light and converts it into a 3D image. Other imaging device well known to a person skilled in the art may of course just as well be implemented.
The surface position may in one embodiment be determined via pixel scanning where via pixel illumination contrast said surface position may be determined.
Alternatively, the second imaging device may be arranged to acquire the 3D image data before the first imaging device acquires the 2D image data.
In an embodiment the first imaging device and the second imaging device may be arranged to simultaneously acquire the 2D image data and the 3D image data, respectively.
Thus, either the 2D data is first analyzed and any anomalies are flagged and their surface positions determined by the image processing unit whereafter the 3D data is analyzed and anomalies flagged. The 2D anomalies are then compared with the 3D anomalies so that the image processing unit can determine whether the anomaly was a true anomaly or a false anomaly. 2D anomalies means possible defaults detected in two-dimensional image data and 3D anomalies means possible defaults detected in three-dimensional image data.
Alternatively, the 3D data is first analyzed, and any anomalies are flagged by the image processing unit and their surface positions determined whereafter the 2D data is analyzed and anomalies flagged. The 3D anomalies are then compared with the 2D anomalies so that the image processing unit can determine whether the anomaly was a true anomaly or a false anomaly.
The 2D data and 3D data may also be analyzed concurrently and anomalies flagged in one data set are compared to the corresponding data set of the other dimensional type.
A further alternative is to use an imaging device that is able to acquire both 2D as well as 3D image data concurrently, thus combining the first imaging device and the second imaging device into one imaging device.
A method for detecting surface characteristics on incoming food objects that may be conveyed by a conveyor apparatus according to the invention comprises the steps of:
The first imaging device may in one embodiment be arranged to acquire the 2D image data before the second imaging device acquires the 3D image, or vice versa, first acquire the 3D data and subsequently the 2D data.
Alternatively, the first imaging device and the second imaging device are arranged to concurrently acquire the two-dimensional image data and the three-dimensional image data.
An advantage of the apparatus and method according to the invention is that false positives, i.e. a wrong indication of a defect present on the scanned surface, may be minimized or even totally avoided. For example, a 2D scan of the surface may detect a colour difference over a certain region, it is uncertain judging from this data whether the indicated defect is a blood discolouration or a hole or a shadow or an indentation/recess. The 3D data obtained from the 3D scan will unambiguously be able to ascertain whether the defect indicated by the 2D data is an actual defect or an indentation or recess present on the surface of the food product.
The aspects and optional details of the invention will be explained below with reference to the drawings. In the drawings:
In
The obtained image data (2D and 3D) are processed in at least one image processing unit 80 which may comprise a computer running image processing data software and having access to the image data stored in a computer memory.
The at least one image processing unit 80 may utilize the 2D image data in determining whether a potential defect is present on the surface of the food object 20. In case such a potential defect property is detected, the processing unit determines a surface position of the potential defect on the food object. Following this, the at least one image processing unit 80 may utilize the 3D image data in determining whether an actual defect is present on the surface of the food object within the determined surface position. For example, the 2D image data may indicate a discoloration at a certain surface location on the food object. The 3D image data may then be utilized to ascertain whether the discoloration is a void (hole or shadow or recess) in the surface or an actual discoloration (e.g. a blood stain).
The at least one image processing unit 80 may utilize an output unit 90, e.g. a display or an automatic message, for outputting defect related data in case both of said 2D and said 3D image data indicate that an actual defect is present on the surface of the food object within the surface position.
Alternatively, the at least one image processing unit 80 may utilize the 3D image data in determining whether a potential defect is present on the surface of the food object 20. In case such a potential defect property is detected, the processing unit determines a surface position of the potential defect on the food object. Following this, the at least one image processing unit 80 may utilize the 2D image data in determining whether an actual defect is present on the surface of the food object within the determined surface position. For example, the 3D image data may indicate a void (hole or shadow or recess) at a certain surface location on the food object. The 2D image data may then be utilized to ascertain whether the void (hole or shadow or recess) in the surface is an actual discoloration (e.g. a blood stain).
A further embodiment of the invention is shown in
In step (S1) 110, two-dimensional image data (2D) of a food object 20 is captured using a first imaging device, and three-dimensional image data (3D) of the food object is captured using a second imaging.
In step (S2) 120, either one of the 2D or the 3D image data is processed to determine whether a potential defect is present on the surface of the food object, where in case such a potential defect property is detected, a surface position of the potential defect is determined.
In step (S3) 130, the remaining one of the 2D or the 3D image data is processed to determine whether an actual defect is present on the surface of the food object within the determined surface position.
In step (S4) 140, defect related data is output in case both of the 2D and the 3D image data indicate that an actual defect is present on the surface of the food object within the determined surface position.
Situation B illustrates no defect at the surface position of the fish fillet as detected by 2D data (arrow points to this surface position). As no defect is determined based on the acquired 3D data, there is no defects inside the fish fillet nor on the surface of the fish fillet and the 2D data indicated a positive result and the spot identified may be e.g. a blood spot or melanin spot.
Situation C illustrates a hole in the fish filled (indicated by the arrow) at the surface position of the black spot as detected from the acquired 2D data. If holes in the fish fillet are accepted the 3D data indicates a false-positive result obtained from the 2D data.
Situation D illustrates something located on the surface of the fish fillet as indicated by the arrow. This may be e.g. a small piece of fish material released from a fish during the processing steps performed before detecting surface characteristics of the fish fillets. Here the fish material stick to the fish fillet and looks like a small bubble on the fish fillet. The material on the fish fillet is not a default of the fish fillet and hereby the 3D data indicates a false-positive result obtained from the 2D data.
Situation B obtained from 3D data illustrates no hole or dirt on the fish fillet, but it shows that the defect are found on a steep part of the fillet. As can be seen in situation B the fish fillet is higher in the left part than in the middle and right part and hereby the fish fillet may not be evenly illuminated when the imaging device capturing two-dimensional image data acquires data. The area which is shadowed may in the 2D data be indicated as a black area, and hereby the 3D data indicates a false positive result obtained from the 2D data.
The above description of possible embodiments of the present invention should not be interpreted as limiting the scope of the present invention.
Number | Date | Country | Kind |
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18181211 | Jul 2018 | EP | regional |
Filing Document | Filing Date | Country | Kind |
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PCT/EP2019/067625 | 7/1/2019 | WO |
Publishing Document | Publishing Date | Country | Kind |
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WO2020/007804 | 1/9/2020 | WO | A |
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Entry |
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Extended Search Report and Written Opinion from European Application No. EP18181211, dated Dec. 19, 2018. |
International Search Report and Written Opinion from PCT Application No. PCT/EP2019/067625, dated Sep. 27, 2019. |
Number | Date | Country | |
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20210112818 A1 | Apr 2021 | US |