Using MATLAB, 9 tasks need to be completed, the original image of the beans will be provided by me. The specification of the tasks are attached bellow.
Using MATLAB, 9 tasks need to be completed, the original image of the beans will be provided by me. The specification of the tasks are attached bellow.
1. Display normalised RGB histogram(s) for your original jellybean image either on a single axis, or on
three separate axes. Perform histogram stretch on the image and show the RGB histogram(s) again.
Calculate and display the RMS contrast before and after the stretch operation.
2. Threshold your histogram-stretched image from question 1 to produce a set of binary images, one for
each jellybean colour you have. You can use any combination of low pass, high pass, band-pass and
band-reject thresholds on one or more channels, as necessary, to identify pixels belonging to each
colour from the background and other unwanted colours. Each binary image should contain a 1 where
that pixel is in the current bean colour, and O otherwise.
Don't worry if the binary images are slightly noisy to start with (i.e., there might be holes in some
jellybeans, or there may be pixels allocated to a particular jellybean colour that shouldn't really be
there). However, do your best to select your threshold values very carefully. Also do this for the
calibration chip you have used.
3. Show the union of the set of binary images you produced in question 2, above. Next show the images
produced when you perform entry-wise multiplication of each of your binary images, and the union of
the binary images, by the original RGB image (i.e., use your binary images as masks to select the
original pixels). If any of the images look particularly poor, go back and revise your threshold values and
threshold methods.
4. Next, we will try to tidy up the binary images we produced in question 3, above. Experiment to see
which of the following methods enable you to more accurately separate pixels belonging to each
jellybean colour from the remaining unwanted pixels: (i) non-linear majority filter, (ii) morphological
erode, dilate, open and close. For the morphological operators, you will also need to experiment with
different structuring elements.
5. Your binary images should have been tidied up by step 4 (i.e., Is only for the beans of interest, with
fewer or no holes), so repeat step 3 to demonstrate this and report on how many pixels are in each
jellybean colour pixel group before and after your selected best-performing method from step 4.
6. Jsing the calibration chip, estimate the area of each bean in mm2. We are doing this to ensure that
there aren't any excessively small, large, or malformed beans on the production line. If there are, we
will reject this batch.
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