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Object tracking one of computer vision. Computer vision similar to human eye function. The difficulty is to detect presence an object and object tracking application made. Object tracking used in aircraft, track cars, human body detectors at airports, a regulator the number of vehicles pass and navigation tools on robots. This study is to identify objects that pass in frame. This research also count the number of objects that pass in one frame. Object tracking done by comparing two algorithms namely Horn-Schunck and Lucas-Kanade. Both algorithms tested using the Source Block Parameter and Function Block Parameter. The test carried out with video resolution 120x160 and the position camera is 2-4 m. The object tracking test is conducted in the duration of 110-120 seconds. Stages tracking object was thresholding, filtering and region successfully obtain object binary video. The Lucas-Kanade has faster in identifying objects compared to the Horn-Schunck algorithm.

ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE