Koyuncu, MuratKoyuncu,M.Cetinkaya,B.Information Systems Engineering2024-07-052024-07-0520150978-146737428-61098-758410.1109/FUZZ-IEEE.2015.73379172-s2.0-84975755284https://doi.org/10.1109/FUZZ-IEEE.2015.7337917https://hdl.handle.net/20.500.14411/3753In this paper, we propose a component-based object detection method extended with the fuzzy inference technique. The proposed method detects constituent components of a complex object instead of a whole object in images. For component detection, multiple multi-class support vector machines (SVM) are used in parallel. Each SVM classifies the candidate component using a different low-level image feature. The obtained results are fused to reach a decision about the component. Then, a fuzzy object extractor determines the whole object considering the detected components and their geometric configurations. The fuzzy object extractor is a fuzzy inference engine which tests various combinations of detected components and their fuzzified directions and distances. The initial tests yield promising results and encourage further studies to extend proposed method. © 2015 IEEE.eninfo:eu-repo/semantics/closedAccessComponent-based object detectionfuzzy inferenceimage processingmultimediasemantic content extractionConference ObjectQ32015-November