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IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper surveys several interesting issues arising in digital geometry due to the need to perform accurate automated measurements on objects that are seen through the eyes of various types of imaging devices. These devices are typically regular arrays of (light) sensors and provide us matrices of quantized probings of the objects being looked at. In this setting, the natural questions that may be posed are: how accurately can we locate and recognize these objects from classes of possible objects, and how precisely can we measure various geometric properties of the objects of interest, how accurately can we locate them given the limitations imposed upon us by the geometry of the sensor lattices and the quantization and noise omnipresent in the sensor device output. Yet another exciting area of investigation is the design of (classes of) objects that enable optimal exploitation of the imaging device capabilities, in the sense of yielding the most accurate measurements possible.