Koyuncu, MuratCetinkaya, BasarInformation Systems Engineering2024-10-062024-10-062015097814673742861544-5615[WOS-DOI-BELIRLENECEK-246]https://hdl.handle.net/20.500.14411/8998In 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.eninfo:eu-repo/semantics/closedAccessComponent-based object detectionfuzzy inferencesemantic content extractionimage processingmultimediaConference ObjectN/AN/AWOS:000370288300118