Developing an eggshell inspection system with computer vision
Computer vision has been widely developed and used in much industry for automatic inspection and robot guidance. This thesis addresses an automatic eggshell inspection and sorting system for helping egg grading process in the poultry industry. The algorithm used for the image processing is divided into two parts: pre-process and main process. Both processes use the combination of thresholding, edge and contour detection, filtering, and blob detection. OpenCV and cvBlobsLib are the main libraries used for developing the software, while the input and output devices will be controlled via parallel I/O ports. Through doing some tests on inspecting random eggs, the results show the overall percentage of 90% total correct detection of separating the eggs into three categories; good, dirty, and cracked.
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