SE0400318D0 - Inspection of cartographic images through multi-layered, neural hybrid classification - Google Patents

Inspection of cartographic images through multi-layered, neural hybrid classification

Info

Publication number
SE0400318D0
SE0400318D0 SE0400318A SE0400318A SE0400318D0 SE 0400318 D0 SE0400318 D0 SE 0400318D0 SE 0400318 A SE0400318 A SE 0400318A SE 0400318 A SE0400318 A SE 0400318A SE 0400318 D0 SE0400318 D0 SE 0400318D0
Authority
SE
Sweden
Prior art keywords
sub
window
layered
inspection
layer
Prior art date
Application number
SE0400318A
Other languages
Swedish (sv)
Inventor
Carl Henrik Grunditz
Lambert Speenenburg
Martin Walder
Original Assignee
Carl Henrik Grunditz
Lambert Spaanenburg
Martin Walder
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Carl Henrik Grunditz, Lambert Spaanenburg, Martin Walder filed Critical Carl Henrik Grunditz
Priority to SE0400318A priority Critical patent/SE0400318D0/en
Publication of SE0400318D0 publication Critical patent/SE0400318D0/en
Priority to PCT/SE2005/000183 priority patent/WO2005078652A1/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks

Abstract

A method for identifying objects on surfaces, comprising the steps of: a) providing a multi-tier neural network having a lower layer (112), a middle layer (114) and an upper layer (116); b) receiving an image of a particular surface to be inspected; c) dividing said image in a number of sub-windows; d) for each sub-window (100), processing said sub-window (100) in said lower layer (112) to derive a plurality of gradient directions in said sub-window (100); e) using said gradient directions in said middle layer (114) to determine at least a first feature for each sub-window (100); f) for each sub-window (100), determining a probability value associated with said at least first feature; and g) for each sub-window (100), using said probability value determined in step f) in said upper layer (116) to determine the presence or absence of at least one type of object on said particular surface. Further, an associated device, integrated circuit and computer program are disclosed.
SE0400318A 2004-02-12 2004-02-12 Inspection of cartographic images through multi-layered, neural hybrid classification SE0400318D0 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
SE0400318A SE0400318D0 (en) 2004-02-12 2004-02-12 Inspection of cartographic images through multi-layered, neural hybrid classification
PCT/SE2005/000183 WO2005078652A1 (en) 2004-02-12 2005-02-11 Method, device, computer program product and integrated circuit for surface inspection using a multi-tier neural network

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
SE0400318A SE0400318D0 (en) 2004-02-12 2004-02-12 Inspection of cartographic images through multi-layered, neural hybrid classification

Publications (1)

Publication Number Publication Date
SE0400318D0 true SE0400318D0 (en) 2004-02-12

Family

ID=31974209

Family Applications (1)

Application Number Title Priority Date Filing Date
SE0400318A SE0400318D0 (en) 2004-02-12 2004-02-12 Inspection of cartographic images through multi-layered, neural hybrid classification

Country Status (2)

Country Link
SE (1) SE0400318D0 (en)
WO (1) WO2005078652A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109063713A (en) * 2018-07-20 2018-12-21 中国林业科学研究院木材工业研究所 A kind of timber discrimination method and system based on the study of construction feature picture depth
JP7211265B2 (en) * 2019-05-22 2023-01-24 日本製鉄株式会社 Identification model generation device, identification model generation method, identification model generation program, steel flaw determination device, steel flaw determination method, and steel flaw determination program

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998008080A1 (en) * 1996-08-20 1998-02-26 Zellweger Luwa Ag Process and device for error recognition in textile surface formations
EP1301894B1 (en) * 2000-04-24 2009-06-24 International Remote Imaging Systems, Inc. Multi-neural net imaging apparatus and method
WO2002097714A1 (en) * 2001-04-09 2002-12-05 Lifespan Biosciences, Inc. Computer method for image pattern recognition in organic material

Also Published As

Publication number Publication date
WO2005078652A1 (en) 2005-08-25

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