Micro Defect Detection on Air-Bearing Surface

Abstract

This chapter presents texture analysis methods for detection of contaminations (micro particle, stain and metal) on the air-bearing surface (ABS). A complete system is developed composed of an image acquisition module, a feature extraction module and a decision-making module. The input ABS image is first analyzed by the texture unit and the co-occurrence matrix to obtain texture features which are then transformed by the principle component analysis (PCA) for effective classification of the defective samples. The chapter detects the contamination particle based on the theory of light scattering technologies: laser, detector and optic. Most light scattering techniques are used for counting particles. J. L. Blesener studied the non-imaging laser particle counter (LPC) for detection of a single particle. B. Bhushan utilized LPC instruments and sampling techniques for detecting and determining the size of particle contamination in rigid disk drives. S. Kochevar proposed the next generation of contamination monitoring using nanotechnology.