Wafer Defect Detection
Detection output on a sample optical lens image: defective regions are segmented and highlighted, with defect classification overlaid
A C++ and OpenCV based computer vision system for automated detection and classification of defects on semiconductor wafer surfaces. Designed to segment defective regions from high-resolution wafer imagery and identify defect type.
Built as a proof-of-concept for inline inspection in semiconductor manufacturing workflows
Setup:
- Clone the repository to your local machine.
git clone https://github.com/vetrivln/WaferDefectDetection
- Add OpenCV to your project:
- Include directories ->
opencv\build\include - Library directories ->
opencv\build\x64\vc16\lib - Link .lib files ->
opencv_world4xx.lib
- Build and Run the project in Visual Studio.
Requirements:
- OS: Windows 10/11 (64 bit)
- Compiler: Visual Studio 2019/2022
- OpenCV: 4.x
- .NET: 4.7.2 or higher