Smartphone-Based Imaging System and Method for Particle Size and Shape Measuring in Baijiu Brewing Process

Yang, Shanlin; Yang, Lin; Xu, DianPing; Zhang, Suyi; Peng, Lihui

doi:10.1109/ist50367.2021.9651363

Cited by 2 publications

(3 citation statements)

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“…That is why the input vector may not be susceptible to small size errors in coffee granules in our application. However, if the applications need to obtain deterministic size values, such as the applications in [13][14][15][16][17][18][19][20], the simple scale calibration using a reference object of known size could not be accurate enough. One should use image acquisition systems with pixel to length scale calibration, ambient brightness control, and a fixed shooting distance.…”

Section: Discussionmentioning

confidence: 99%

“…From the concepts of image acquisition and image data transfer and remote servers, an application to precisely measure particle size and shape in the Baijiu (Chinese liquor) brewing process using a smartphone-based imaging system [14] is similar to our system, but they need a specially built image acquisition platform with an accurate scale calibration of pixel to length. In that paper, without applying artificial intelligence, smartphones on a custom image acquisition platform can take photographs at a fixed distance using a custom designed APP to transfer the photos and communicate with the server and display the results.…”

Section: Discussionmentioning

confidence: 99%

“…The devices should be able to fix the shooting distance between the camera and the objects, control the ambient brightness during photography, and have a calibrate function to determine the scale of the image pixels to the actual length. For example, custom-built image-capturing platforms [13][14][15], microscopes with acquisition software [16][17][18][19], and high-resolution digital CCD industrial cameras with acquisition software [20] have brightness controls and known calibrated pixel to length ratios. In our case, for user convenience, by using a flash light, the coffee granule images are able to be taken by mobile phones at a distance roughly between 15 and 25 cm without precise pixel to length calibration.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Remote Access Server with Chatbot User Interface for Coffee Grinder Burr Wear Level Assessment Based on Imaging Granule Analysis and Deep Learning Techniques

Chen,

Lin,

Tseng

et al. 2024

Applied Sciences

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Coffee chains are very popular around the world. Because overly worn coffee grinder burrs can downgrade the taste of coffee, coffee experts and professional cuppers in an anonymous coffee chain have developed a manual method to classify coffee grinder burr wear so that worn burrs can be replaced in time to maintain the good taste of coffee. In this paper, a remote access server system that can mimic the ability of those recognized coffee experts and professional cuppers to classify coffee grinder burr wear has been developed. Users only need to first upload a photo of coffee granules ground by a grinder to the system through a chatbot interface; then, they can receive the burr wear classification result from the remote server in a minute. The system first uses image processing to obtain the coffee granules’ size distribution. Based on the size distributions, unified length data inputs are then obtained to train and test the deep learning model so that it can classify the burr wear level into initial wear, normal wear, and severe wear with more than 96% accuracy. As only a mobile phone is needed to use this service, the proposed system is very suitable for both coffee chains and coffee lovers.

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