Distorted grid recognition with its application to microarray image analysis

In this paper, we address a novel automatic distorted grid recognition algorithm and its application to identify spots grid in microarray images. The proposed method contains two main steps. The first step is a top-down procedure which retrieves the global information, horizontal spacing, vertical spacing and rotation angle, of grid by utilizing Gaussian mixture model and document spectrum. The second step, which is bottom-up, rebuilds the grid structure with the aid of the data obtained in the first step. The estimation of global information is precise and the reconstruction progress is effective. The accuracy and efficiency of the approach are validated by applying it to synthesis images, real distorted grid and microarray images. Furthermore, our approach is automatic and insensitive to the absence of grid elements.

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