Image Processing Reference
FIGURE 6 RGB image.
5.1.4 Indexed images
Each pixel has a value that does not give its color but an index to the color in the map which
has a list of all the colors used in that image.
6 Project design
The procedure followed to obtain the interruption whether for the red violation or the speed
Image Acquisition : The proposed design was performed through recording a video by using
a digital camera with a focus of 14 mm then converting this video to a series of images in order
to obtain the principle of image processing through MATLAB 7.7.0 version. Whereas all the
images obtain will be JPEG format.
• Cropping : The basic type of preprocessing refers to image cropping. Cropping refers to the
removal of the outer parts of an image to improve framing, accentuate subject mater or
change aspect ratio. In other words, it refers to removing unwanted areas from a digital
image capture. This is needed in the project in the part of the vehicle registration plate.
Image cropping can be performed either by manually or by defining the selected spatial
coordinates [ a b c d ]. a is the pixels from left, b is the pixels from botom, c is the width of
the selected area, and finally d is the height of the selected area.
• Bwarea Function : This function from the MATLAB basically removes from a binary image
all the connected components (objects) which are lower than the defined pixel. After which
it will reproduce another binary image with the entire pixel that are higher or equal to the
Segmentation : Segmentation is the process of assigning a label to every pixel. In other words,
the segmentation is partitioning a digital image into multiple segments "pixels." The goal of
segmentation is to simplify the representation of an image into something that is more mean-
ingful and easier to analyze. Whereas the result of image segmentation is a set of segments
that cover the entire image, or a set of contours extracted from the image. The simplest meth-
od of image segmentation is called the threshold method. This method is based on threshold
value to turn a grayscale image into a binary image. During this process, every pixel in an im-
age is called as object pixel if the value is greater than the threshold value and it is named as
background pixel if the value is lower than the threshold value. An object pixel is being given
a “1” value while the background pixel is given the “0” value. After which a binary image is
being created with all the object and background pixels.
Representation and Description