博士 / 國立高雄科技大學 / 工學院工程科技博士班 / 108 / This research adopts computer vision technology, OpenCV (Open Source Computer Vision), combined with K-means in machine learning to propose an intelligent shrimp counting system that can quickly calculate the number of the shrimps. In the case of considering the higher flexibility and lower cost of this application, we introduce the emerging technologies of serverless and IoT (Internet of Thing) such as AWS (Amazon Web Service) Lambda and Raspberry Pi. This research is, therefore, mainly designed to apply the computer vision to undertake the counting of shrimps automatically. OpenCV provides plenty of computer vision applications and often cooperates with the Raspberry Pi and AWS Lambda. The steps of image processing for accurately counting the shrimps are as follows: (1) capture the image, (2) filter and remain the sampling color, (3) threshold the filtered image, (4) contour the blobs in the image (5) determine the area of one shrimp (6) count the number of the shrimps. Concerning the performance and flexibility, we embed the image process into AWS Lambda function. Experimental results of counting shrimps (Neocaridina heteropoda var. red) show that our proposed application completes the counting operation of 150 shrimps in 0.1 second and the accuracy is up to 95%.
| Identifer | oai:union.ndltd.org:TW/108NKUS0028001 |
| Date | January 2019 |
| Creators | Yeh, Chi-Tsai, 葉期財 |
| Contributors | Chen, Ming-Chih, 陳銘志 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 100 |
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