Patent ID: 8363933
Filing Date: 2013-01-29
Classification: G06K,H04N

Abstract:
1. An image identification method, comprising steps of: learning separating hyperplanes respectively indicating boundaries of each category by reading a training data image including a plurality of blocks of the training data image to each of which a category is labeled and calculating image feature quantity of each of the plurality of blocks of the training data image; dividing a newly acquired image into a plurality of blocks to produce a plurality of block images; calculating the image feature quantity of each of the plurality of block images of the newly acquired image by its color space information and frequency component; determining a category for each of the plurality of block images of the newly acquired image based on a distance of the image feature quantity from the separating hyperplane of each category; grouping neighboring blocks of the same category together to form a group of blocks; and checking whether the determined category for each of the groups of blocks meets inconsistent condition for judging inconsistency of physical relationship between categories stored in an inconsistent condition table or not, based on physical relationship between a targeted group of blocks and other group of blocks surrounding the targeted group of blocks and for which other category is determined.