Obtain the images Suzi$1.$bin and ct$\_$scan. bin from the course web site. Each image has $256$

$256$ pixels and each pixel has $8$ bits.

In this assignment you will perform object extraction $($target extraction$)$ by using simple thresh$-$

olding followed by connected components labeling $($blob coloring$)$ with minor region removal. This

is a special case of two classical image processing problems known as image segmentation and clas$-$

sification. Throughout the assignment, including the printing of your results, use a value of $255$

$($Hex $0$xFF$)$ for LOGIC ONE and a value of zero $($Hex $0$x$00)$ for LOGIC ZERO.

Objectives:

Suzil: the first objective is to produce a binary image $J$ that is LOGIC ONE at pixels

contained in the "girl" object of the original image and LOGIC ZERO at pixels contained in

the background of the original image. The second objective is to produce a grayscale image

$K$ of the segmented "girl" object. At pixels where $J$ is LOGIC ONE, $K$ should be equal to

the original Suzif image. At pixels where J is LOGIC ZERO, K should be $255($to make a

"white background" for the segmented object image$).$

ct$\_$scan: the first objective is to produce a binary image $J$ that is LOGIC ONE at pixels

contained in the "torso section" object of the original image and that is LOGIC ZERO at

pixels contained in the background of the original image. The second objective is to produce

a grayscale image $K$ of the segmented "torso section" object. This should be done exactly

the same way it was for the Suzil image.

For each image, use the following procedure:

A$)$ Study the image and select an appropriate threshold that will discriminate between the desired

object and the background.

B$)$ Form a binary image $J$ by applying the threshold so that pixels likely to be part of the desired

object are assigned the value LOGIC ONE, while those likely to be part of the background

are assigned the value LOGIC ZERO.

Hint: for the Suzi$1$ image, this means that $J(i,j)$ should be LOGIC ONE if the corresponding

input pixel is below threshold. For the $c{t}_{-}$scan image the opposite is true: you should set

$J(i,j)=$ LOGIC ONE if the corresponding input pixel is above threshold. This is because

the object of interest in the Suzil image is darker than the background, whereas the object

of interest in the ct$\_$scun image is brighter than the background.

C$)$ Apply connected components labeling with minor region removal $($as described at pp$.2\mathrm{.}40-$

$2\mathrm{.}47$ of the course notes$)$ to refine the segmentation in $J,$

D$)$ Construct the segmented object grayscale image $K.$