Food Appearance Inspection | Viewing Shape, Color, Chips, and Foreign Objects through Images
In food appearance inspection, what can be captured in images includes shape and size, browning and color variations, chips and cracks, and foreign objects on the surface. Since even good products differ from one another, it is more suitable to learn the range of permissible variations rather than matching to a fixed shape. Foreign objects inside, as well as taste and texture, cannot be determined from appearance and require different methods. 【Points】 ■ Shape, color, chips, and surface foreign objects can be handled with images. ■ Due to significant individual differences in good products, the permissible range is determined by AI or standards. ■ Foreign objects inside, as well as taste and texture, cannot be identified from appearance. *For detailed explanations, please refer to the technical notes and downloadable materials in the related links.
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【Contents of this Technical Note】 ■ The aspects of food that can be captured in images are shape, color, chips, and surface foreign objects. ■ The difficulty in inspecting food lies in the fact that no two good products are the same shape. ■ Browning, contours, and chips are 2D, while thickness and bulging are 3D. ■ How to use AI for food with significant individual differences. ■ The arrangement of food, overlapping, and the color of the belt change the visible range. ■ Foreign objects inside, taste, and texture cannot be determined through appearance inspection. ■ A method to verify the range of good products using actual food items. 【Consultation】 We will confirm whether it can be measured or captured with your work by checking the actual items. Please consult us with a photo.
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The technical notes can be read by anyone from the related links. We will consult regarding the costs of development and testing based on the details provided.
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【Frequently Asked Questions】 Q. Can the judgment of browning be adjusted to match human assessment? A. By quantifying the color and comparing it with samples that humans deem acceptable, it can be aligned. This assumes that the lighting and photography are stable. Q. Can foreign objects mixed in food be detected through images? A. If they are on the surface and differ in color or shape, they can be found. However, foreign objects buried inside or those that are the same color as the ingredients are difficult to detect visually. Q. Can we start even if we don't have a collection of defective samples? A. It is sometimes possible to start by gathering a large number of good products and looking for outliers. However, to confirm any missed detections, having at least a few defective samples would be beneficial.
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We specialize in 2D and 3D inspection and measurement technologies using cameras. We possess a wide range of knowledge in optics, mechanics, electronics, and software, enabling us to provide technical support for both hardware and software. Not only do we have personnel with experience working as researchers at image inspection device manufacturers, major electronic component manufacturers, and universities, but we also have numerous successful implementations of developed products in actual production environments, making our ability to adapt advanced technology to on-site needs a strong point. Additionally, we are skilled not only in developing proprietary algorithms but also in using off-the-shelf products such as image processing controllers from Keyence and Omron, allowing us to excel in selecting and utilizing the most suitable equipment for specific needs. In recent years, while AI technology has garnered attention, there are cases where utilizing 2D and 3D technologies can be implemented more easily than AI, and cases where optical devices and mechanical jigs can improve performance and reduce software load. We offer services related to image systems, including "equipment selection," "implementation support," "performance improvement of existing equipment," "technology development," and "joint development," so please feel free to consult with us first.


