VEHICLE DETECTION FROM REMOTE SENSING IMAGES | ||||
| Nuclear Sciences Scientific Journal | ||||
| Article 9, Volume 2, Issue 1, 2013, Page 133-137 PDF (1.1 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/nssj.2013.30989 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| IRAKY H. KHALIFA; ABDUALRHMAN A. ALZIDAN | ||||
| Fac. Computers and Information, Helwan Univ | ||||
| Abstract | ||||
| Image object detection is an important application of remote sensing technology. Road vehicle detection using very high-resolution remote sensing images has a unique advantage of covering a large area such as jaddah and alriad at the same time over all ground-based detectors. But the detection of small vehicle-object in remote sensing imagery is still a challenging task. Several parameters of gray values and sizes are examined to classify the objects in the image. The vehicles and their associated shadows can be discriminated by removing big objects such as roads. Our test shows a promising result of detecting the vehicle. We present an object-based detection approach with IMAGINE Objective for the detected vehicles in the study area. (jeddah city , alriad city ) IMAGINE Objective employs feature models working on objects produced by image segmentation and various other pixel-based algorithms can be processed by geometric and textural parameters after being vectorised. This process is used and optimised for the extraction of the vehicles from high resolution images. Preliminary object detection tests using a semi automated post-classification approach show reliable results. For this research, the applied methods prove to be useful to detect vehicles on the road of example images even without producing a complete extraction of all vehicles. The approach will be extended to the whole images area. | ||||
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