Magnetic disk inspection using texture recognition

Quality control in magnetic disk production is a crucial issue, in particular the condition of the head disk `interface´ which is critical to the overall quality of the final product. The verification of this `interface´ has been complicated by advances in technology which have seen the height at which the head glides above the disk, the fly-height, reduce to micron order. This has necessitated inspection of the disks for defects of comparable magnitude. There is a growing need for visual inspection which is low cost and computationally fast in order to achieve total quality control. The micrograph of the disk surface is a natural texture and, whilst defect boundaries can be perceived by human inspectors, they do not correspond to a local discontinuity in intensity. Conventional edge detection operators are therefore unsuitable for segmentation. In this paper, segmentation is achieved via texture recognition. A texture recognition method based on a co-occurrence spectrum of n^th order is used and defect boundaries are defined by discontinuities in the texture within a window scanning the image