Applying the basic image processing method professor discussed in the lecture and familiarizing us with programming with images.
1.Create a grayscale image of your face by converting your color image using one of the conversions we discussed in class last week.
2.Flip your face image horizontally, i.e. left to right, right to left.
3.Come up with a third way of manipulating your face that produces an interesting output.
Method and Implementation
1. To create a grayscale image I simply scan every pixels of the origin image and use the average value of the three channels (Red, green and blue) as the value of new gray image. By this way I get the grayscale image.
2. To flip the image I also scan the whole origin image and I put the values of every rows on the opposite side of the flipped image and so call flip the image.
3. Firstly, I set the size of my scanning window as 3 by 3. So the value of every pixels in the new picture is the average value of 8 neighbors of it. And with the hint homework, I literate the scanning for 3 times to amplify the results. In this way we get a blurred version of gray image.
|Trial||Source Image||Result Image|
Discuss your method and results:
- What are the strengths and weaknesses of your method?
- Do your results show that your method is generally successful or are there limitations? Describe what you expected to find in your experiments, and how that differed or was confirmed by your results.
Time costing. Since basically all of my algorithm have to go through the whole picture. The time costing of it is pretty huge. In this case, I have to wait for a long time to get the result.
The blur algorithm meet some problems. When I compute the average value of some pixels, I get the 0 value and cannot figure out why.
After applying the method professor discussed in the lecture, I realize that most of the processing on image are based on pixels. Pixels are the smallest unit we manipulate our algorithm.