Towards digital manufacturing : improving image resolution through feature detection methods
Machine Automation plays a vital role in all in many applications in this scientifically advanced era, especially in manufacturing industry. A typical example would be iPhones. In the 2017 fiscal year, Apple sold 216.76 million iPhones [1] . It is therefore understood that a tiny mistake will cause...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/10356/76278 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Machine Automation plays a vital role in all in many applications in this scientifically advanced era, especially in manufacturing industry. A typical example would be iPhones. In the 2017 fiscal year, Apple sold 216.76 million iPhones [1] . It is therefore understood that a tiny mistake will cause companies at such scale a huge loss. One in many ways that we can reduce such error is through improving machining precision and accuracy. One possible method of approaching such precision is with the help of an “artificial eye”, 3D scanning and processing the image thereafter to make the machines smarter. Such improvement could be introduced by exploring deeper into Image Processing. Images from an interest area or object can provide the manufacturer with a good amount detail and use, if it is processed properly. The processed image could be used to give the physical robot spatial awareness through “hand-eye” calibration. In this report, the methods to match a relatively unclear image to High Definition (HD) images and Method to synchronize the robot’s coordinate system and the camera coordinate system (“Hand-Eye calibration”). The “hand” here would refer the robot’s and the camera is the “eye”. |
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