
This paper presentsa comparative studyof descriptors keypoint algorithms doinga combinationof detectors anddescriptors. We combined the SIFT, SURF and Harris detector algorithms with the SIFT and SURF descriptor algorithms.Three experimentswith images withdifferent characteristicswere performed,intwo of theseexperimentswere usedimages of realobjects, in athird experiment, some degradationin an imagesuch asscale reduction, rotation, blurring, darkening andaddition ofnoisehave beenperformed, to analyze the behaviorof the algorithms. Experiments were also performed withalldegradationstogether.Toanalyze theproposedcombination, we extractedprocessing timeand the number ofinliers. This workcontributes toapplicationsthat requireusing keypoint descriptors algorithms in detection andrecognitionof objects inimages.
Object Recognition, Q1-390, Reconhecimento de Objetos, Science (General), Keypoint Detector, TA1-2040, Engineering (General). Civil engineering (General), Detector de Pontos Chave, Descritor de Pontos Chave, Local Features, Keypoint Descriptors, Características Locais
Object Recognition, Q1-390, Reconhecimento de Objetos, Science (General), Keypoint Detector, TA1-2040, Engineering (General). Civil engineering (General), Detector de Pontos Chave, Descritor de Pontos Chave, Local Features, Keypoint Descriptors, Características Locais
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