Team Assignment HW#5

Muhammad Irsyadi Firdaus (P66067055)

Iva Nurwauziyah (P66067021)

1. Develop an image segmentation algorithm to segment the Potomac River from the

multi-spectral image of Washington DC showed below (4 channels: R, G, B, NIR).

B channel ( =0.45-0.52) G channel ( =0.52-0.6)

R channel ( =0.63-0.69) Near Infrared channel ( =0.76-0.9)

Figure 1. The original image

Image segmentation means division of an image into meaningful structures. It

is process of extracting and representing information from the image to group

pixels together with region of similarity. Watershed based image segmentation

algorithms are less computational complex and provide very good segmentation

results. Watershed transformation also called, as watershed method is a powerful

mathematical morphological tool for the image segmentation.

First, we generate the Normalized Difference Water Index (NDWI) using this

following formula:

𝑁𝐷𝑊𝐼 = 𝐺𝑟𝑒𝑒𝑛 − 𝑁𝐼𝑅

𝐺𝑟𝑒𝑒𝑛 + 𝑁𝐼𝑅

Where, NDWI refers to the water index image, NIR refers to spectral value of

pixels at the near infrared spectral channel (band 4), and green refers to spectral

value of pixels at the green spectral channel (band 2).

Then, calculate threshold using global thresholding method. This threshold set

by trial and error until getting the best result, so we obtain the best threshold value

is 0.5. The value means the maximum region visualize of the river with less noise

in the around. The increase of threshold value will be less noise. In this threshold,

there are still has a noise, so we need to do removing this noise using erosion and

continued with opening method, and also provide the radius value. The radius is 2

for the erosion and opening, respectively.

After that, we continue to visualize the river in blue color. All of this result

will showed in the figure 3.

Figure 2. The threshold image = 0.5

2. Visualize the segmented river in colors and output the area of the segmented river

in pixel.

Figure 3. GUI Segmentation River