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One of the current challenges in the analysis of a very large number of images acquired using cryo-electron microscopy is to investigate fast, accurate approaches for automatic detection of biological particles. Cross-correlation with a reference image based techniques have been developed in the past for this purpose; both computational requirements and accuracy, however, have limited their applicability to only a very small set of particles. The paper describes a new computational framework for fast, automatic particle detection, through the application of edge detection and a sequence of ordered Hough transforms. In particular, it presents how to adapt the generalized Hough transform to efficiently detect approximately rectangular shapes in a cluttered background. Preliminary results using hemocyanin as a model particle are promising.