Images were aligned over the trees by aligning the first image with a yield tree

using a flagpole. The truck was moved back and forth so that the camera field of view

was aligned with the flagpole. Subsequent non-overlapping images were obtained using

the encoder. The encoder was calibrated and programmed to prompt the user on reaching

the next location for taking non-overlapping image. At this location the truck was stopped

for a brief period and an image was taken. Images of most of the tree canopy were

acquired by driving around the trees on both sides. Images were processed on a Windows

based system with a 750 1VHz Pentium processor.

 3.4 Image Analysis using HSI Color Model

 Color is one of the most important properties that humans use to discriminate

between obj ects and to encode functionality. For example, sky is blue, citrus fruit is

orange, and leaf is green. An obj ect' s color comes from the interaction of light waves

with electrons in the obj ect matter (Nassau, 1980). The colors that human beings identify

in an obj ect are based on the nature of the light reflected from the obj ect surface. For

example, a red apple reflects light from wavelengths centered around 700 nm ranges,

while absorbing most of the energy at other wavelengths. An obj ect that reflects light in

the entire visible spectrum equally appears white in color.

 The purpose of a color model is to define a standard specification for specifying

color in some generally accepted way. For instance, the red, green, and blue (RGB) color

model is used in hardware applications like PC monitors, cameras and scanners; the cyan,

magenta and yellow (CMY) color model is used in color printers; and the luminance, in-

phase and quadrature (YIQ) model is used in television broadcasts. The most commonly

used color models for image processing are RGB and HSI models. In essence, a color