Abstract:
We proposed a ceramic tile flaw detection system to improve quality control. Manual flaw detection is less accurate due to human error and industrial environment. We proposed an automatic tile damage detection approach.
As photos are taken in varied lighting. A way to eliminate light from an image helps detect cracks accurately. Noise is removed during image pre-processing. Convert picture to binary. Create a vertical line structuring element and dilate the binary image.
The crack will be bolder after dilation. The technology discovers cracks and undesired objects through image analysis. To detect only cracks, we remove undesirable items from image using MATLAB inbuild. Fill gaps after deleting unneeded items.
System finds cracks using connected components. System reveals tile damage. Show image with crack bounding box. One tile took about 2 seconds to process. an impressive result shows that an automated approach can replace manual ceramic tile detection with greater accuracy and efficiency. The proposed technique detects defective tile 85% of the time.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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