Act 3: Image types and basic image enhancement

For this activity, we were required to collect images of various formats. For this, I have chosen the following:


Binary: the "John Hancock" signature
(image courtesy of http://upload.wikimedia.org/wikipedia/commons/thumb/9/90/JohnHancockSignature.svg/384px-JohnHancockSignature.svg.png)





Greyscale: Charlie Chaplin
(image courtesy of http://www.europeancourier.org/118.htm)














Indexed: Van Gogh's "Starry Night"
(image courtesy of http://www.wpclipart.com/art/Paintings/Van_Gogh/VanGogh_starry_night.png.html)











True Color: the Great Barrier Reef
(image courtesy of http://www.gmcc-09.com/welcome-to-melbourne/the-country/)









Aside from finding various images on the internet, we are also required to scan an object, preferably with a distinct border. Along with Earl, I used a map of Japan:

except in my activity, I chose Kyushu to be my region of interest. The image was binarized, and the following image was obtained:

It is now possible to apply the follow function in order to obtain the contour of the image so that it becomes possible to apply the Green’ s theorem and obtain the area of the image. The area can also be computed by taking the sum of the image since the binary image is simply composed of ones, which represent the white parts of the image, and zeroes, which represent the black parts of the image. Hence, the area of the image is effectively its sum.

The obtained values were:
using Green's theorem: 17946 pixels
using summation: 18600 pixels
% deviation: 3.5161%

The values obtained are sufficiently close to each other. By taking the length of the scale in terms
of pixels, the area of Kyushu can then be calculated by mere conversion.

I will give myself a grade of 10/10 for this activity since the previously learned lessons were successfully applied for this activity. I would like to thank Earl for sharing with me his scanned image of Japan.