Comments on Others:
The paper proposes a new low-level recognition and beautification system to recognize 8 primitive shapes as well as combinations of these primitives with recognition rate at 98.56%. The Paleo process initiates with a pre-recognition calculation and after that sending these to lower-level shape recognizes for further processing. Each of these low-level recognizer correspond to a particular primitive shape then returns a Boolean flag to specify whether the recognizer passed or failed as well as a beautified shape object that best fits the input stroke. After all shapes are executed, are hierarchy function sorts each interpretation of the order of a best fit. The pre-recogntion eliminates duplicate points and then create series of graphs including directional graph, speed graph, curvature graph and corners based on a simple corner finder algorithm. In addition this phase computes 2 new features called NDDE and DCR to defer polylines from curves.
After using the Paleo in our first class project, I’m much satisfied with its processing capabilities w.r.t sketch recognition. It’s a powerful corner finder tool to get the basic primitive shapes of a sketch that you can apply towards devising other sketch recognition algorithms, (which makes life much easier). With my personal experience on hand writing recognition, I feel Paleo is a successful way of doing the preprocessing of an image for other low level tasks. I used to apply image processing techniques like binarization and skelatanizaton and then fuzzy rules to get primitive shapes and, yes, things are daunting that way.
I’m just wondering whether Paleo is capable of giving few more of feature properties of interests??? Things like positive/negative slanted line, horizontal/vertical line, U-like, inverse U-like, V-like and inverse V like??? I’m not sure paleo is already doing this or not, but if so, things are pretty good for a new character recognition pre-processing task using PaleoSketch………..
Find the paper here.