urvey of Methods and Str in Character Segmentation
Richard G. Casey, Éric Lecolinet · 1996
been developed, rather than to simply list sources. Segmentation methods are listed under four main headings. What may be termed the classical approach consists of methods that partition the input image into subimages, which are then classified. The operation of attempting to decompose the image into classifiable units is called dissection. The second class of methods avoids dissection, and segments the image either explicitly, by classification of prespecified windows, or implicitly by classification of subsets of spatial features collected from the image as a whole. The third strategy is a hybrid of the first two, employing dissection together with recombination rules to define potential segments, but using classification to select from the range of admissible segmentation possibilities offered by these subimages. Finally, holistic approaches that avoid segmentation by recognizing entire character strings as units are described. This paper provides a review of these advances. The aim is to provide an appreciation for the range of techniques that have