ISPRS Commission III, Vol.34, Part 3A ,,Photogrammetric Computer Vision“, Graz, 2002 
  
ASSESSMENT OF TWO CHEAP CLOSE-RANGE 
FEATURE EXTRACTION SYSTEMS 
a 
Ahmed Elaksher , Mohammed Elchezali, Ashraf Saved, and Yasser Eimanaditli” 
a all ; ; ; ; 
School of Civil Engineering, Purdue University, West Lafayette, IN 47906-1284, USA elaksher@ecn purdue.edu 
b ud : 
Faculty of Engineering, Cairo University, Giza, Egypt 
ABSTRACT 
The use of non-metric cameras in photogrammetric applications is considered under very strict constraints due to their instability and 
lack of fiducial coordinate system. Architectural building documentation, monuments registration, and monitoring structure 
deformations are very essential close-range photogrammetric applications that require high accuracy and quick data acquisition. 
Using metric cameras, in such situations, is quite uneconomic and non-metric cameras are in favor. In order to accelerate the 
processing time of analyzing non-metric cameras digital techniques are preferred. 
The aim of this research is to investigate the use of two inexpensive techniques for object reconstruction using digital images 
produced by non-metric cameras. The first technique employs an inexpensive 35mm camera and a cheap scanner, while a low-cost 
digital camera is used in the second technique. Both techniques are thoroughly evaluated and the RMS errors are investigated. 
Results show that the 6-paramter transformation model is the best model to handle geometric errors introduced by scanners. The 
object reconstruction process results show that sub millimeter accuracy, in object coordinates, can be achieved if systematic errors 
are considered. 
1. INTRODUCTION 
The basic task of many photogrammetric systems is to derive 
object space coordinates from 2D images. Analog, semi- 
analytical, and analytical techniques have been employed for 
a long period of time in photogrammetry to extract ground 
coordinates of objects from hardcopy images. In recent years, 
digital techniques are implemented in photogrammetric 
applications. The advantages of using digital techniques are: 
the ease and speed of data acquisition, the inherent on-line 
and real-time capabilities, and the high degree of automation. 
Acquiring digital images is done either by scanning hardcopy 
images or by capturing the photographs directly in digital 
format using digital sensors. 
The aim of this paper is to investigate the process of 
capturing ground features digitally through one of the 
following schemes: scanning hardcopy images produced by 
non-metric 35mm cameras or acquiring digital images 
directly using non-metric digital cameras. Each technique is 
evaluated and analyzed using a number of mathematical 
models that relate image space coordinates with ground 
space coordinates. The implemented mathematical models 
were adapted to handle the systematic errors produced by 
non-metric cameras. 
2. PREVIOUS WORK 
In (Boron, 1996) the accuracy of the UMAX 1200 scanner is 
investigated; the correction method he proposed reduces the 
scanning errors from +5 pixels to £0.15 pixels. The 
correction is executed in two stages. First order corrections 
are found for each point in the scanner plate first then the 
second order corrections for each run are determined. In 
(Bolte et. al, 1996) both the geometric and radiometric 
properties of the scanners were studied. The RM -1 scanner 
was used and it was found that its accuracy is equivalent to 
the analytical plotter. 
In (Karras and Mavrommati, 2001) the effects of the radial 
distortions in the 35mm cameras is studied. A number of 
approaches, ranging from the utilization of linear features to 
the rectification of regular grids, were used. It was shown 
that ignoring the radial lens distortion increases the RMS 
errors dramatically. In (Cruz et. al, 2000) the inner 
orientation of non-metric cameras was investigated. The 
35mm camera images were scanned at 600 dpi and 1200 dpi. 
A comparison between the 6-parmeters and 4parameters 
coordinate transformation models showed that the former 
transformation model is better than the later. 
In (Seedahmed and Schenk, 1998) a bundle adjustment with 
self-calibration scheme is presented for calibrating a high 
accuracy CCD digital camera. An extended version of the 
collinearity equations was implemented with corrections for 
the symmetric distortion, the decentering distortion, the 
image plane unflatness, and the in-plane image distortion. 
The results showed the necessity to correct systematic errors. 
In (Zolfaghari and Malian, 2000) non-metric cameras are 
used to record architectural and historical buildings. The 
work shows the effectiveness of using non-metric cameras 
for capturing this type of features. 
Section 2 presents the calibration process of flatbed scanners. 
Section 3 summarize the mathematical models used to 
transfer image coordinates to ground coordinates. The object 
reconstruction process is presented in section 4. Conclusions 
are discussed in sections. 
2. GEOMETRIC CALIBRATION OF FLATBED 
SCANNERS 
During the scanning process, the positions of the scanned 
features are corrupted causing the distances between them to 
change. For cheap scanners, the distortions increase due to 
the bad functioning of the mechanical, optical, and electronic