Matches in SemOpenAlex for { <https://semopenalex.org/work/W2020192013> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W2020192013 abstract "Nowadays, image segmentation is of great importance in features extraction and object recognition forvideo image sequence. Many traditional segmentation techniques have special application and exists somelimitation in some degree. After analyzing the advantages and disadvantages of the present imagesegmentation and object recognition methods, according to the characteric of infrared image, this paperproposes a very simple yet effective algorithm to optimize the threshold value, which is in accordance withthe status of the reference pixels. The proposed algorithm varies the threshold value with bidirectionalline-by-line scanning (the forward scanning and the backward scanning) fusion model. The purpose of thetechnique is to discriminate targets from the background, which is equivalent to assigning the label F(representing foreground) to object pixels, and the label B (representing background) to backgroundpixels. Based on these bidirectional scanning intersections in the corresponding regions, this paper appliesthe conditional probability density function (PDF) to fuse and optimize the threshold value. At the sametime, the optimal threshold values for target segmentation and recognition were acquired. Therefore, thispaper designs a novel background frame differencing method that refers to previously conclusions made byneighboring pixels. Change different infrared image sequences, the experiment results show this fusionmethod can eliminate the boundaries blurring, especially the transition regions between object (foreground)and background. As a conclusion, for different infrared image sequences with complex illumination change,noise change, etc., the proposed method gives better segmentation and recognition results for objects thanother traditional methods, such as the fixed threshold method, the single directional scanning technique,and so on. On the other hand, the proposed method has lower complexity and higher real-time, which ishelpful for hardware design and engineering application." @default.
- W2020192013 created "2016-06-24" @default.
- W2020192013 creator A5015716594 @default.
- W2020192013 creator A5020697004 @default.
- W2020192013 creator A5021344350 @default.
- W2020192013 creator A5086912139 @default.
- W2020192013 date "2009-07-03" @default.
- W2020192013 modified "2023-09-27" @default.
- W2020192013 title "Image segmentation and object recognition based on bidirectional scanning fusion technique" @default.
- W2020192013 cites W1533162639 @default.
- W2020192013 cites W2013759484 @default.
- W2020192013 cites W2070630810 @default.
- W2020192013 cites W2161763247 @default.
- W2020192013 cites W2502894931 @default.
- W2020192013 doi "https://doi.org/10.1117/12.834114" @default.
- W2020192013 hasPublicationYear "2009" @default.
- W2020192013 type Work @default.
- W2020192013 sameAs 2020192013 @default.
- W2020192013 citedByCount "0" @default.
- W2020192013 crossrefType "proceedings-article" @default.
- W2020192013 hasAuthorship W2020192013A5015716594 @default.
- W2020192013 hasAuthorship W2020192013A5020697004 @default.
- W2020192013 hasAuthorship W2020192013A5021344350 @default.
- W2020192013 hasAuthorship W2020192013A5086912139 @default.
- W2020192013 hasConcept C115961682 @default.
- W2020192013 hasConcept C124504099 @default.
- W2020192013 hasConcept C153180895 @default.
- W2020192013 hasConcept C154945302 @default.
- W2020192013 hasConcept C160633673 @default.
- W2020192013 hasConcept C25694479 @default.
- W2020192013 hasConcept C2781238097 @default.
- W2020192013 hasConcept C31972630 @default.
- W2020192013 hasConcept C41008148 @default.
- W2020192013 hasConcept C65885262 @default.
- W2020192013 hasConcept C67561299 @default.
- W2020192013 hasConcept C89600930 @default.
- W2020192013 hasConcept C99498987 @default.
- W2020192013 hasConceptScore W2020192013C115961682 @default.
- W2020192013 hasConceptScore W2020192013C124504099 @default.
- W2020192013 hasConceptScore W2020192013C153180895 @default.
- W2020192013 hasConceptScore W2020192013C154945302 @default.
- W2020192013 hasConceptScore W2020192013C160633673 @default.
- W2020192013 hasConceptScore W2020192013C25694479 @default.
- W2020192013 hasConceptScore W2020192013C2781238097 @default.
- W2020192013 hasConceptScore W2020192013C31972630 @default.
- W2020192013 hasConceptScore W2020192013C41008148 @default.
- W2020192013 hasConceptScore W2020192013C65885262 @default.
- W2020192013 hasConceptScore W2020192013C67561299 @default.
- W2020192013 hasConceptScore W2020192013C89600930 @default.
- W2020192013 hasConceptScore W2020192013C99498987 @default.
- W2020192013 hasLocation W20201920131 @default.
- W2020192013 hasOpenAccess W2020192013 @default.
- W2020192013 hasPrimaryLocation W20201920131 @default.
- W2020192013 hasRelatedWork W1939935747 @default.
- W2020192013 hasRelatedWork W1966411054 @default.
- W2020192013 hasRelatedWork W1973469270 @default.
- W2020192013 hasRelatedWork W1981023434 @default.
- W2020192013 hasRelatedWork W2018114028 @default.
- W2020192013 hasRelatedWork W2037935319 @default.
- W2020192013 hasRelatedWork W2071779119 @default.
- W2020192013 hasRelatedWork W2072364240 @default.
- W2020192013 hasRelatedWork W2073805073 @default.
- W2020192013 hasRelatedWork W2110302973 @default.
- W2020192013 hasRelatedWork W2126178892 @default.
- W2020192013 hasRelatedWork W2132989324 @default.
- W2020192013 hasRelatedWork W2139488721 @default.
- W2020192013 hasRelatedWork W2153731472 @default.
- W2020192013 hasRelatedWork W2160694455 @default.
- W2020192013 hasRelatedWork W2171533969 @default.
- W2020192013 hasRelatedWork W2189625685 @default.
- W2020192013 hasRelatedWork W2192721210 @default.
- W2020192013 hasRelatedWork W2280008878 @default.
- W2020192013 hasRelatedWork W2575240214 @default.
- W2020192013 isParatext "false" @default.
- W2020192013 isRetracted "false" @default.
- W2020192013 magId "2020192013" @default.
- W2020192013 workType "article" @default.