#### Howdy, Stranger!

It looks like you're new here. If you want to get involved, click one of these buttons!

# The distribution of transmitting power is shown in

The final result of clustering is given in Table 4. In this example, 2 clusters are generated at the end. Since it NU7441 requires at least 3 data points to form an area; i.e. th2=3, the cluster formed by data 7 and 8 is ignored.
2.1. Detection of damage contour areas
A list of group(s) with group member(s) are clustered using the autoclustering method described above. Now it is required to generate contour of each group such that all points of this group are either inside the contour or on the boundary. Convex hull is one of the algorithms for determining the smallest convex set containing a discrete set of points. This algorithm also applies to a polygon, or just any set of line segments, whose hull is the same as the hull of its vertex point set. The most popular “Graham scan” algorithm  is applied in this work for determining convex polygon as damage zone. Now whether a point(pixel) is inside a polygon or not can be found out by the algorithm described below. Contour diagram is useful to find the pixel location (inside/outside) with respect to damaged section.
Fig. 5 presents few points (a, b, c, d, e, f, g) in the vicinity of a polygon. The following steps needs to be carried out to check point?s location (inside/outside) with respect to polygon:?Draw a horizontal line to the right of each point and extend it to infinity.?Count the number of times the line intersects with polygon edges.?A point is inside the polygon if either count of intersections is odd or point lies on an edge of polygon. If none of the conditions is true, then point lies outside.
Fig. 5. Location of a point (pixel) with respect to contour.Figure optionsDownload full-size imageDownload as PowerPoint slide
3. Experimental results for extracting the damage information of the sample
The above algorithms are applied to determine damage zone(s) of experimental cubical samples made of concrete having size of 150 mm. These samples are prepared in the laboratory and one vertical face of each sample is speckled using the procedure developed by Deb and Bhattacharjee . A universal testing machine (UTM) of 3500 kN capacity is used to compress the experimental sample at a loading rate of 0.45 mm/min. A high precision data acquisition system mentioned in  is used to capture the required data in the experiment. A Logitech Carl Zeiss Tessar HD 1080P full HD web camera is used to seamlessly capture images of the speckled face with increment of loading. Fig. 6b shows a damaged sample obtained during the test. This image is processed with the algorithms described earlier and finally the bounded damage zone is determined (Fig. 6f) which will help to identify the pixels inside the damaged zone and Cotransfection will be omitted for calculating deformation/strain using DIC technique.