Image Feature Extraction for Wafer Analysis Using JMP's Python Integration (2025-US-PO-2427)Wafer visualization is critical in semiconductor manufacturing for defect analysis, process optimization, and yield improvement. This work introduces a method for automated feature extraction from bulk image data sets using JMP's integrated Python environment. By leveraging image processing libraries such as OpenCV, RGB features are extracted at consistent coordinates of the images to generate wafer color maps for further statistical analysis. This integration of JMP and Python demonstrates a practical solution for interpreting bulk wafer image data.
Automation and ScriptingData Exploration and Visualization
