Contour Based Tracking for Driveway Entrance Counting System

Managing vehicle in free-flow entrance is tiring to do manually by a guard control especially due to the increase in transportation demand. Providing an accurate vehicle counting approach is vital for traffic management and it will surely be an essential part in tomorrow's smart cities. Therefore, the main objective of this paper is to propose a more accurate vehicle counter by using the tracking and heuristic rules approaches. EzCam v1.0 is a vehicle surveillance system for a free-flow entrance where a module of vehicle counting based on proposed idea has been applied. The proposed method does not require high computational resources more than any relatively affordable non task specific hardware. It employs single threshold, contour extraction and sequential frame analysis and finally, vehicle counting process subsequently. The tracking-based method employs foreground object detection method and a mechanism for object filtering approach as compared to Chris Dahms approach which does not consider any object rejection and accept all contour information as relevant to be counted as vehicles. As a result, EzCam v1.0 which utilizes the exploited contour-based approach is able to achieve up to 94 percent of accuracy rate and outperforms the classic Chris Dahms method which obtained an accuracy of 88 percent. Therefore, the Exploited Contour based tracking method helps vehicle counting system to perform better accuracy in comparison to Chris Dahms approach

EXPLOITABLE EDGE ANALYSIS FOR FREE FLOW VEHICLE PLATE LOCALIZATION

In Malaysia, vehicle recognition system (VRS) such as vehicle plate recognition and counting, is rapidly growing and applied in many areas such as to identify vehicle identities for the law enforcement by authorities and electronic toll collection by highway agencies. Uncovering the region of interest in chaotic illumination environment at free flow road makes localizing license plate is critical process of VRS. Available edge vertical projection claimed to be robust to illumination, however, it tends to create false edges and sensitive to noises that can hinder the recognition performance. Thus, this research aims to propose a license plate localization method that based on exploitable edge analysis.comprising four main steps, namely pre-processing, rectangular blob searching, analysis and the vertical rectangular blobs projection. It calculates total and exploit edge information at y axis of the image. The proposed method is then tested on the European number plate datasets i.e. Baza Slika which contains about 167 vehicle images and Ondrej which contains about 97 vehicle images. The experimental results show that the proposed method outperforms the Ondrej method by obtaining accuracy of 95% on Baza Slika dataset and slightly lower by an accuracy of 91% on the Ondrej dataset. Then, the proposed method tested on the Malaysia vehicle dataset namely Tol Sungai Long data set which contains about 584 images of different illumination conditions, i.e. 297 images in the morning, 140 images in the afternoon and 147 images in the night. The proposed method outperforms other approaches with accuracy of 91.24%, 93.57% and 75.51% in the morning, evening and night respectively

Eksploitasi unjuran pinggir untuk penyetempatan plat kenderaan bebas laluan

Di Malaysia, sistem pengecaman kenderaan (SPK) seperti pengecaman plat kenderaan dan pengiraan kenderaan berkembang pesat di pelbagai bidang seperti mengenal pasti identiti kenderaan bagi tujuan penguatkuasaan oleh pihak berkuasa keselamatan dan sistem kutipan tol elektronik oleh agensi-agensi lebuh raya. Menemui kawasan diminati dalam suasana illuminasi berselerak di jalan bebas laluan menyebabkan mengesan plat kenderaan menjadi rumit dalam SPK. Kaedah unjuran pinggir dikatakan lasak kepada illuminasi namun, ia cenderung mencipta pinggir palsu dan peka kepada kebisingan yang mengancam kepada prestasi pengecaman. Justeru, kajian ini bermatlamat untuk mencadangkan satu kaedah penyetempatan plat kenderaan menggunakan ekspoitasi unjuran pinggir yang mengandungi empat langkah utama iaitu pra-pemprosessan, carian blob segi empat, analisis dan projeksi menegak blob-blob segi empat. Ia mengira jumlah informasi pinggir yang terdapat dalam blob pada setiap paksi-Y dalam imej. Kaedah penyetempatan ini kemudiannya diuji menggunakan set data plat kenderaan Eropah iaitu set data Baza Slika yang memilik 167 imej kenderaan dan set data Ondrej yang memiliki 97 imej kenderaan. Hasil kajian menunjukkan kaedah cadangan mengatasi kaedah cadangan Ondrej dengan skor ketepatan 95% pada set data Baza Slika dan sedikit rendah pada set data Ondrej iaitu 91% skor ketepatan. Selanjutnya, kaedah cadangan diuji menggunakan set data plat Malaysia iaitu Set Data Tol Sungai Long yang memiliki 584 imej kenderaan berbeza situasi pencahayaan, iaitu 297 imej pada waktu pagi, 140 imej pada waktu petang dan 147 imej pada waktu malam. Kaedah cadangan mengatasi kaedah penanda aras yang lain dan skor ketepatan sebanyak 91.24%, 93.57% dan 75.51% pada masing-masing waktu pagi, petang dan malam