INTELLIGENT MACHINE VISION SYSTEM FOR ROAD TRAFFIC SIGN RECOGNITION

Abstract We proposed an intelligent machine vision system to recognize traffic signs captured from a video camera installed in a vehicle. By recognizing the traffic signs automatically, it helps the driver to recognize the signs properly when drivig, to avoid accidents caused by mis-recognized the traffic signs.The system is divided into two stages : detection stage to localize signs from a whole image, and classification stage that classifies the detected sign into one of the reference signs. A geometric fragmentation technique, a method somewhat similar to Genetic Algorithm (GA) is employed to detect circular sign. Then a ring partitioned method that divides an image into several ring-shaped areas is used to classify the signs. From the experimental results, the proposed techniques are able to recognize traffic sign images under the problems of illumination changes, rotation, and occlusion efficiently. Keywords : Machine vision, traffic sign recognition, geometric fragmentation, ring partitioned matching

Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification

The paper describes a colour-based segmentation method of European traffic signs for detection in an image and a feature-based recognition method for categorizing them into given classes. At first, we have performed analysis of several well-known colour spaces as the RGB, HSV and YCbCr often used for segmentation purposes. The HSV colour space has been chosen as the most convenient for segmentation step and colour-based models of traffic signs representatives were created. Next, the fast radial symmetry (FRS) detection method and the Harris corner detector were used to recognize circles, triangles and squares as main geometrical shapes of the traffic signs. For these purposes a new gallery of real-life images containing traffic signs has been created and analysed. Overall efficiency of our recognition method is approx. 93 % on our gallery and is usable for real-time implementations

Sistem Pemandu Pengemudi Berbasis Kamera Embeded

Keamanan dan kenyamanan berkendara merupakan salah satu aspek penting yang harus diperhatikan oleh industri otomotif. Sebuah sistem yang mampu memberikan peringatan dini pada pengemudi akan membantu mencegah terjadinya kecelakaan. Sistem pemandu pengemudi (Driver assistance system) merupakan sistem yang dikembangkan untuk menyediakan fungsi tersebut. Sistem pemandu pengemudi berbasis kamera merupakan sistem yang berkembang cukup pesat, seiring dengan perkembangan teknologi di bidang teknik pengolahan citra digital dan sistem komputer. Penelitian ini bertujuan untuk mengembangkan sistem pemandu pengemudi berbasis kamera yang mampu mendeteksi kelelahan dan konsentrasi/pandangan mata pengemudi, rambu-rambu lalu lintas, dan marka jalan, serta objek atau kendaraan yang berada di depan. Pada peneltian di tahun pertama, dikembangkan sistem pendeteksi kelelahan pengemudi menggunakan kamera embeded yang dipasang di ruang kemudi kendaraan. Sebuah sistem komputer embeded digunakan sebagai pengolah utama dalam proses pendeteksian berbasis kamera tersebut. Dengan menggunakan sistem embeded ini, implementasi sistem di kendaraan dapat dilakukan dengan mudah dan murah