02343nam a2200241 a 4500 vtls000040366 KUKTEM 20251114204455.0 090715t2009 my po f m 000 0 eng d THE0006944(Local) 201906131146 aida 201107132243 VLOAD 200908141648 VLOAD 200908141628 VLOAD 200907151105 kam UMP TK7872.D48 N35 2009 rs Bc. Wan Najwa Wan Ismail Object detection system using haar-classifier / Wan Najwa Binti Wan Ismail Object detection system using haar-classifier [electronic resource] Kuantan, Pahang : UMP, 2009 59 p. : ill. (some col.) ; 30 cm. + 1 computer disc Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2009 The invention of new algorithms had encouraged to the reinforcement of image processing’s application. An algorithm for the design object detection systems is presented. Haar-classifier is utilized as the algorithms for this object detection system. The exertion of Haar-Classifier had boosted to the upgrade system which is faster and more accurate. In this system, Haar-Classifier is conjunct with the Adaboost machine learning algorithms wherefore the performance of the system is upgraded. Development of this project is categorized into two phase which are training phase and execution phase. Training phase use OpenCV utilities such as haartraining.exe to train the object by calculating the object’s weak constraints. This is for the purpose of finding the different features of the object of interest. The list of these weak constraints is converted to the xml file to be included in the coding which had been developed using Visual Studio 2005. The execution process will result on the detection process of object of interest. System will detect rounded image in any image which had been included in the system itself. Object detection system using Haar-classifier algorithm can perform best performance of high detection rate and high level of accuracy rate. Detectors 0 0 0 1 20000 20000 2019-09-04 0 TK7872.D48 N35 2009 rs Bc. 0000037856 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 20000 20000 2019-09-04 0 CD 3303 | TK7872.D48 N35 2009 rs Bc. 0000037857 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 2665 2671 VTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5200*6500*9992