Matches in SemOpenAlex for { <https://semopenalex.org/work/W4306409841> ?p ?o ?g. }
Showing items 1 to 61 of
61
with 100 items per page.
- W4306409841 abstract "Abstract Nowadays, kinship verification is considered an attractive research area with a great interest in computer vision. It significantly affects applications in the real world, such as finding missing individuals, forensics, and genealogical research. However, verifying kinship relations between people using facial images is not straightforward. Many limitations affect kinship verification accuracy. Therefore, this paper proposes a new approach for verifying kinship based on facial image analysis. The proposed approach goes into six stages: preprocessing, feature extraction, feature normalization, feature fusion, feature representation, and kinship verification. The preprocessing stage is responsible for converting RGB images into other color models. Different types of handcrafted feature descriptors (i.e., color and texture descriptors) are extracted in the feature extraction stage. The texture features are represented by scale invariant feature transform (SIFT), local binary pattern (LBP), and heterogeneous auto-similarities of characteristics (HASC), whereas the color features are represented by color correlogram (CC) and dense color histogram (DCH). Then, all the features are set to the same range in the feature normalization stage to be suitable for feature fusion. The feature fusion stage takes place where the different types of features are concatenated together. Next, in the feature representation stage, the parent and child features are gathered into one feature vector. Finally, the kinship verification stage produces the final decision of being kin or non-kin using the gentle AdaBoost ensemble classifier. KinFaceW-I and KinFaceW-II datasets were used to evaluate the proposed approach, where the obtained results were 79.54% and 90.65%, respectively. It is noteworthy that the proposed approach outperforms many state-of-the-art approaches that verify kinship, including those dependent on metric learning and deep convolutional neural nets (CNNs)." @default.
- W4306409841 created "2022-10-17" @default.
- W4306409841 creator A5041008898 @default.
- W4306409841 creator A5054497823 @default.
- W4306409841 creator A5066199951 @default.
- W4306409841 date "2022-10-17" @default.
- W4306409841 modified "2023-09-28" @default.
- W4306409841 title "Enhanced kinship verification analysis based on color and texture handcrafted techniques" @default.
- W4306409841 doi "https://doi.org/10.21203/rs.3.rs-2139523/v1" @default.
- W4306409841 hasPublicationYear "2022" @default.
- W4306409841 type Work @default.
- W4306409841 citedByCount "0" @default.
- W4306409841 crossrefType "posted-content" @default.
- W4306409841 hasAuthorship W4306409841A5041008898 @default.
- W4306409841 hasAuthorship W4306409841A5054497823 @default.
- W4306409841 hasAuthorship W4306409841A5066199951 @default.
- W4306409841 hasBestOaLocation W43064098411 @default.
- W4306409841 hasConcept C115961682 @default.
- W4306409841 hasConcept C136886441 @default.
- W4306409841 hasConcept C138885662 @default.
- W4306409841 hasConcept C144024400 @default.
- W4306409841 hasConcept C153180895 @default.
- W4306409841 hasConcept C154945302 @default.
- W4306409841 hasConcept C19165224 @default.
- W4306409841 hasConcept C2776401178 @default.
- W4306409841 hasConcept C34736171 @default.
- W4306409841 hasConcept C41008148 @default.
- W4306409841 hasConcept C41895202 @default.
- W4306409841 hasConcept C52622490 @default.
- W4306409841 hasConcept C53533937 @default.
- W4306409841 hasConcept C87335442 @default.
- W4306409841 hasConceptScore W4306409841C115961682 @default.
- W4306409841 hasConceptScore W4306409841C136886441 @default.
- W4306409841 hasConceptScore W4306409841C138885662 @default.
- W4306409841 hasConceptScore W4306409841C144024400 @default.
- W4306409841 hasConceptScore W4306409841C153180895 @default.
- W4306409841 hasConceptScore W4306409841C154945302 @default.
- W4306409841 hasConceptScore W4306409841C19165224 @default.
- W4306409841 hasConceptScore W4306409841C2776401178 @default.
- W4306409841 hasConceptScore W4306409841C34736171 @default.
- W4306409841 hasConceptScore W4306409841C41008148 @default.
- W4306409841 hasConceptScore W4306409841C41895202 @default.
- W4306409841 hasConceptScore W4306409841C52622490 @default.
- W4306409841 hasConceptScore W4306409841C53533937 @default.
- W4306409841 hasConceptScore W4306409841C87335442 @default.
- W4306409841 hasLocation W43064098411 @default.
- W4306409841 hasOpenAccess W4306409841 @default.
- W4306409841 hasPrimaryLocation W43064098411 @default.
- W4306409841 hasRelatedWork W132579780 @default.
- W4306409841 hasRelatedWork W144668168 @default.
- W4306409841 hasRelatedWork W1981015757 @default.
- W4306409841 hasRelatedWork W2085553065 @default.
- W4306409841 hasRelatedWork W2396912247 @default.
- W4306409841 hasRelatedWork W2550539038 @default.
- W4306409841 hasRelatedWork W2752642517 @default.
- W4306409841 hasRelatedWork W3003836766 @default.
- W4306409841 hasRelatedWork W3101572448 @default.
- W4306409841 hasRelatedWork W4253160043 @default.
- W4306409841 isParatext "false" @default.
- W4306409841 isRetracted "false" @default.
- W4306409841 workType "article" @default.