Image Processing Reference

In-Depth Information

Fig. 13.5
Converting the RGB image to a gray-scale image

Fred had calibrated the robot to the table, so that the robot could pick up coins

if their position on the table were provided. The position of the coins found by

the image processing software therefore needed to be mapped into the coordinate

system of the table, i.e. the robot. From the system they developed for the bartender

they knew the solution was to find four corresponding points in the two coordinate

systems and then find the mapping using the theory of homography. To increase the

precision of the mapping they decided to use 16 points instead of four. They placed

16 coins on the table in a regular grid spanning the entire table. They first measured

the position of each coin with respect to the origin of the table (defined to be the

lower left corner) and then measured their positions in the image. They now had 16

corresponding points, which they loaded into a program they found on the web and

hocus-pocus, out came the coefficients of Eq. 10.12. They put the coefficients into

Eqs. 10.13 and 10.14 and they could now map from the image coordinates to the

coordinates of the robot. Now they just needed to find the coins and their type.

13.3 Preprocessing

The first idea that came to mind when they discussed how to distinguish the different

types of coins from each other was to use the color of the coins. Fred, however,

quickly undermined that idea by showing them how the color of a coin can change

after being exposed to different circumstances such as extensive sunlight or acid.

Having accepted that they decided to convert the input RGB image to a gray-scale

image in order to reduce the amount of data. They played around with different

weighting schemes, see Eq. 3.3, but in the end it turned out that simply using the

red part of the image, that is
W
R
=

0, gave the best result.

They argued among themselves that the reason was that the coins contains more red

material.
1
In Fig.
13.5
the conversion is illustrated.

1 and
W
G
=

W
B
=

1
The explanation could of course also be that the lighting in the scene is more reddish, but they

never investigated that.