Word spotting via spatial point processes

This paper presents a statistically based method for spotting target words in documents. The crux of the method is the representation of a word by a spatial (planar) point process evolving on a regular lattice of coordinate pairs. This is accomplished by extracting the coordinate pairs, i.e. pixel locations, where the binary bitmap values of the word are non-zero. With this representation the word is completely determined by the spatial intensity function, i.e. the unnormalized spatial probability density function, associated with the extracted set of coordinate pairs. In this work, we use a finite number of moments of the intensity function to characterize the word. Location and scale invariance are obtained by transforming the coordinate pairs to have zero mean and unit variance. Finally, optimal detection strategies are applied to the moments to make the decision.