Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
- PDF / 1,272,322 Bytes
- 10 Pages / 600 x 792 pts Page_size
- 69 Downloads / 171 Views
Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers Antonio Berlanga Departamento de Inform´atica, EPS, Universidad Carlos III de Madrid, 28911 Legan´es, Madrid, Spain Email: [email protected]
Juan A. Besada GPDS, Departamento Se˜nales, Sistemas y Radiocomunicaci´ones, ESTIT, Universidad Polit´ecnica de Madrid, 28040 Madrid, Spain Email: [email protected]
´ Garc´ıa Herrero Jesus Departamento de Inform´atica, EPS, Universidad Carlos III de Madrid, 28911 Legan´es, Madrid, Spain Email: [email protected]
Jose´ M. Molina Departamento de Inform´atica, EPS, Universidad Carlos III de Madrid, 28911 Legan´es, Madrid, Spain Email: [email protected]
Javier I. Portillo GPDS, Departamento Se˜nales, Sistemas y Radiocomunicaci´ones, ESTIT, Universidad Polit´ecnica de Madrid, 28040 Madrid, Spain Email: [email protected]
Jose´ R. Casar GPDS, Departamento Se˜nales, Sistemas y Radiocomunicaci´ones, ESTIT, Universidad Polit´ecnica de Madrid, 28040 Madrid, Spain Email: [email protected] Received 18 December 2002; Revised 13 October 2003; Recommended for Publication by Sergios Theodoridis The design of statistical classification systems for optical character recognition (OCR) is a cumbersome task. This paper proposes a method using evolutionary strategies (ES) to evolve and upgrade the set of parameters in an OCR system. This OCR is applied to identify the tail number of aircrafts moving on the airport. The proposed approach is discussed and some results are obtained using a benchmark data set. This research demonstrates the successful application of ES to a difficult, noisy, and real-world problem. Keywords and phrases: aircraft recognition, evolutionary strategies for OCR, statistical pattern classifier, image processing.
1.
INTRODUCTION
We describe the design of an image-based aircraft identification system for an advanced surface movement guidance and control systems (A-SMGCS) [1, 2]. This work is aimed at implementing some functions of the A-SMGCS concept in Madrid-Barajas international airport, in order to provide aircraft identification. A-SMGCS requires the unambiguous identification of all aircraft and vehicles in the airport movement area. Cameras for this function should be deployed near taxiways and runways, in positions being traversed for
all the interest targets, prior to their entrance into the area to be controlled (mainly runways and taxiways). When an aircraft passes in front of the camera (which may be predicted using a tracking system), an image of its tail is captured. An optical character recognition (OCR) applied over aircraft tail number is used to identify aircraft [3, 4]. In this paper, it is proposed to tune the parameters of the statistical classifier used in the OCR applying an evolutionary computation algorithm. Then, the aircraft identification algorithm is applied and the tracking system is updated with this information. This process is shown in Figure 1.
1126
EURASIP Journal on Applied Signal Processing
Tracking sys
Data Loading...
