3D Model Registration-Based Batch Wafer-ID Recognition Algorithm

Abstract

Wafer identification (ID) is a serial number printed on the surface of wafer, which is used for indexing production process data in manufacture execution system. The automatic recognition of wafer ID is helpful to improve the level of automatic production. However, the existing equipment and methods mainly focus on single wafer-ID recognition, which require wafers to be taken out and placed on a specific platform, resulting in low efficiency. In this paper, we present a batch wafer-ID recognition method based on machine vision, including a specific designed image-acquisition system and recognition algorithms. Based on the priori information, we formulate a 3D model for the cassette and wafers to be registered with the features extracted from the image. Combined with image-processing techniques, the pose of wafers in the cassette is estimated to undistort the perspective deformation of wafer-ID characters, such that we can exploit a classic lightweight convolution neural network for character recognition. The proposed system can capture and recognize the whole image of a cassette of wafers at once, which does not need to take out the wafers from the cassette and avoids the risk of contamination. Extensive experiments were conducted to evaluate the performance of our proposed techniques by collecting the data set of wafer-ID images. The results show that our proposed 3D model-based rectification method can correct the character deformation effectively and enable the lightweight classifier to achieve high speed and high accuracy for batch wafer-ID recognition.

Keywords

• Optical character recognition
• wafer identification
• machine learning
• model registration