%0 Journal Article %1 IJACSA.2012.031011 %A Navjot Kaur Sheetal Kundra, Harish Kundra %D 2012 %J International Journal of Advanced Computer Science and Applications(IJACSA) %K Feature Shape extraction. prediction; recognition; %N 10 %T Shape Prediction Linear Algorithm Using Fuzzy %U http://ijacsa.thesai.org/ %V 3 %X The goal of the proposed method is to develop shape prediction algorithm using fuzzy that is computationally fast and invariant. To predict the overlapping and joined shapes accurately, a method of shape prediction based on erosion and over segmentation is used to estimate values for dependent variables from previously unseen predictor values based on the variation in an underlying learning data set.

@article{IJACSA.2012.031011, abstract = {The goal of the proposed method is to develop shape prediction algorithm using fuzzy that is computationally fast and invariant. To predict the overlapping and joined shapes accurately, a method of shape prediction based on erosion and over segmentation is used to estimate values for dependent variables from previously unseen predictor values based on the variation in an underlying learning data set.}, added-at = {2014-02-21T08:00:08.000+0100}, author = {{Navjot Kaur Sheetal Kundra}, Harish Kundra}, biburl = {https://www.bibsonomy.org/bibtex/25d6d42a1722ca97f5e15321e1d9da8d9/thesaiorg}, interhash = {94459ed5aa3a30c3b42af6a1e9fb544f}, intrahash = {5d6d42a1722ca97f5e15321e1d9da8d9}, journal = {International Journal of Advanced Computer Science and Applications(IJACSA)}, keywords = {Feature Shape extraction. prediction; recognition;}, number = 10, timestamp = {2014-02-21T08:00:08.000+0100}, title = {{Shape Prediction Linear Algorithm Using Fuzzy}}, url = {http://ijacsa.thesai.org/}, volume = 3, year = 2012 }