In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
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4. DEVELOPMENT 
Inputs such as images, digital topographic mapping and 
software are needed to perform the work. The materials used 
and the methodology are presented as follows. 
4.1 Materials 
The ALOS images and the topographical mapping comprising 
the study area are shown in Figure 01. This area lies at Paraná 
(Brazil) state, specifically in the municipality district of 
Guaraque^aba, Brazil, near the coastline. 
The area is bounded between the coordinates UTM: 
• Upper left: 
Latitude -25° 11'25.95" 
Longitude -48° 22' 00.20" 
• Bottom right: 
Latitude: -25° 17'05.17" 
Longitude -48° 14'37.92" 
The ALOS images were acquired through the research program 
of the Brazilian Institute of Geography and Statistics (IBGE), 
which is responsible for distributing the ALOS images for 
federal government agencies, research institutions and other 
non-commercial users in Brazil. The software used is the ENVI 
4.5 and MATLAB R2007b. The ENVI 4.5 allows the 
manipulation of ALOS images as well as the topographic 
mapping; the MATLAB is used for the development of routines 
that take the mathematical morphology. 
4.2 Methodology 
The roads extracted were not pavement and belonging to PR - 
405. To obtain the field reality, topographic maps at 1:25.000 
scales were used to identify the roads on the scene. From the 
step 01 to step 03, the processing was performed in the software 
ENVI 4.5. 
STEP 01 - REGISTRATION: The registration is required for 
the integration of images acquired by different sensors, for 
example the AVNIR-2 and PRISM, integration of images 
obtained at different times, among other applications. For its 
implementation is necessary to choose control points. After 
collection of control points, which must be distributed across 
the entire image, is needed to define the interpolation process. 
In this work the bilinear interpolation method was chosen. 
STEP 02 - FUSION: The images available are of different 
sensors, in this case AVNIR-2 and PRISM and with different 
spatial resolution, 10 meters and 2.5 meters respectively. Thus, 
for the analysis of mixed spatial databases, which may consist 
of images from different sensors with different spatial 
resolutions, it is necessary to perform the fusion process. Fusion 
was performed by principal components. After obtaining the 
principal components, the first component is removed and 
placed in the panchromatic image, in this case the PRISM 
image. After PRISM assume to be the first principal component 
is necessary to reverse transformation to return the multispectral 
bands. 
STEP 03 - CLASSIFICATION: This step is performed the 
classification of the image obtained in the fusion process. The 
method used was the supervised classification, where the 
classes of information are pre-defined, and from its definition 
are acquired samples of each class. To perform the 
classification, classifiers are needed. The classifier used was the 
statistical Maximum Likelihood - ML. The classified image is 
used for verification of stretches of roads which are not possible 
to identify with the PRISM image. 
From the step 04, all processes have been developed in 
MATLAB. 
STEP 04 - EXTRACTION: An initial selection of stretches of 
road is done using algorithms of mathematical morphology and 
segmentation. For this process has generated a routine for the 
PRISM image binarization. Armed with binary image the 
morphological operators were applied to it. Operators of 
closing, erosion were applied. Several tests using different 
structuring elements were performed to find the best solution 
for the image used. At this stage, most other classes, such as 
vegetation, are eliminated. To eliminate other unwanted traces 
of features the connected components of the image were 
calculated and the smallest areas excluded. The product of this 
post-processing was a cleaner image of traces of unwanted 
features. However, at this moment the road obtained has not 
complete linear features, performing inconsistently. 
STEP 05 - FILLING: Was developed a routine to complement 
the road obtained in extraction (step 04). This routine used 
other techniques of mathematical morphology and an algorithm 
for calculating the Euclidean distance. From a User-defined 
threshold, based on the calculated Euclidean distance, the road 
extracted was completed. At the end the images (PRISM binary 
code, classified, filled) were overlaid to verify the areas filled by 
the algorithm. 
5. RESULTS 
The methodology has been applied and the results were as 
follows. Initially the PRISM image panchromatic was binary 
code in MATLAB and the road cut into two parts. For this 
result was used a threshold equal to 90. This threshold is 
defined as object to be extracted in the image. After the 
application of morphological operators like dilation, was not