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Image detection is one of the crucial issues in image processing besides feature extraction and recognition (Bataineh, Abdullah, & Omar, 2011, 2012). Computer surveillance such as license plate recognition (Romero, Prabuwono, & Taufik, 2011) is an example of object detection application. To ensure that the selected and determined objects were correctly obtained, a very strategic way for object detection is highly required (Abdullah, PirahanSiah, Abidin, & Sahran, 2010; Prabuwono & Idris, 2008). Several prominent ways License Plate Detection (LPD) were for contour detection (Han, Han, Wang, & Zhai, 2003), Hough transform (Soh, Chun, & Yoon, 1994), Radon transform (Shapiro, Gluhchev, & Dimov, 2006), Morphology (Xu & Zhu, 2007), clustering (Siah, 2000; Abdullah, Khalid, Yusof, & Omar, 2007; Abdullah et al., 2010; PirahanSiah, Abdullah, & Sahran, 2011; Abidin, Abdullah, Sahran, & PirahanSiah, 2011) and Speed Up Robust Features (SURF) (Bay, Tuytelaars, & Van Gool, 2006). However, this paper will elaborate on the theories and applications of only some of the mentioned techniques for object detection. Later, these techniques are experimented and compared.
The rest of the paper is organized as follows. Related works and proposed method are discussed in subsequent sections. Then, we justify our proposed work in the Results and Analysis section. This paper concludes our findings in the Conclusion section.