Tiny surface defect inspection of electronic passive components using discrete cosine transform decomposition and cumulative sum techniques

Passive components, owing to their low or no power consumption, are widely used in modern electronic devices. Nevertheless, tiny defects that often appear in the surface of passive components impair not only their appearances but also their functions. This paper proposes a global approach for the automated visual inspection of tiny surface defects in SBL (Surface Barrier Layer) chips, whose random surface texture contains no repetitions of basic texture primitives. The proposed method, taking advantage of the DCT decomposition and the cumulative sum techniques, does not requires textural features, the lack of which often limits the application of feature extraction-based methods. We apply the cumulative sum algorithm to the odd–odd matrix that gathers most power spectra in the decomposed DCT frequency domain, and select the large-magnitude frequency values that represent the background texture of the surface. Then, by reconstructing the frequency matrix without the selected frequency values, we eliminate random texture patterns and retain anomalies in the restored image. Experimental results demonstrate the effectiveness of the proposed method in inspecting tiny defects in random textures.