http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CA-1301351-C

Outgoing Links

Predicate Object
assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ce7c6d5242ed96052e0864b1064119e8
classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-41
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-40
filingDate 1989-02-23-04:00^^<http://www.w3.org/2001/XMLSchema#date>
grantDate 1992-05-19-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_547feaf7922b49d3502f72627e96b921
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6d2e27fa011120d6d7143361d02116bd
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_5722d440d3b14212a8e0d871f798285b
publicationDate 1992-05-19-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CA-1301351-C
titleOfInvention Optimum fast textural feature extractor
abstract "OPTIMUM FAST TEXTURAL FEATURE EXTRACTOR" ABSTRACT OF THE DISCLOSURE The invention is situated in the general field of computer image analysis; it relates to a textural parameter extractor for classification or learning. Four (4) simple 2D optimum masks independent of image, are applied to four adjacent pixels in order to diago-nize the associated covariance matrice. The first three (3) central moments, namely absolute deviation, standard deviation and skewness for each transformed image constitute a feature vector of twelve (12) components for classification purposes. Parallel and Sequential structures are also presented for fast textural feature extractor applications.
priorityDate 1988-03-23-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

Incoming Links

Predicate Subject
isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419557597
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID1983

Total number of triples: 17.