Multi-focusing algorithm for microscopy imagery in assembly line using low-cost camera

We propose an algorithm to perform multi-focus image fusion and integrate a set of images acquired at different focus settings to a single uniformly focused image for visual inspection in assembly lines. The goal of image fusion is to integrate complementary image multi-view information from standard, low resolution assembly line camera into one new image, the quality of which could not be achieved using other methods such as direct digital photography. Our method is based on the image decomposition into Gaussian pyramids, generation of the Laplacian pyramids, and image reconstruction from the Laplacian pyramids. The main characteristics of the proposed method include good quality of integrated multi-focus image, and suitability for microscopy conveyor applications given movement of objects, different lighting conditions, and positional misalignments. We have evaluated our method using eight image quality metrics yielding good results (best results were obtained using the Tenengrad (TENG) method, reaching an accuracy of 0.982) with a low-cost camera and computationally efficient implementation.