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CINDY 186Applied Physics One-Eight-Six Digital Image Processing Class National Institute of Physics University of the Philippines Diliman, Quezon City
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Applied Physics One-Eight-Six Digital Image Processing Class National Institute of Physics University of the Philippines Diliman, Quezon City
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CINDY 186 | ccesporlas-ap186.blogspot.com Reviews
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Applied Physics One-Eight-Six Digital Image Processing Class National Institute of Physics University of the Philippines Diliman, Quezon City
CINDY 186: September 2009
http://ccesporlas-ap186.blogspot.com/2009_09_01_archive.html
Wednesday, September 9, 2009. Activity 17 Photometric Stereo. Figure 1. Photometric Stereo. Equation 1. Intensity at point P(x,y). In this activity, we use four images of an object taken with different light source positions and use it to reconstruct the 3D structure of the illuminated area, as shown by Figure 2. Figure 2. Images of object at different light source positions. To calculate for the surface normal of the object we need to get the far away point source locations given by V. The human brain m...
CINDY 186: October 2009
http://ccesporlas-ap186.blogspot.com/2009_10_01_archive.html
Monday, October 5, 2009. Activity 18 Noise Models and Basic Image Restoration. Image restoration is a basic image processing application where an image that has been degraded or damaged is being recovered. To recover the image, the degradation must be known and thus can be used in restoring the image. Figure 1. PDFs of different noise types. Figure 2. Types of filtering used. Figure 3. Test image and its PDF. Figure 4 shows the noisy image for the added Gaussian noise with mean = 0.5 and standard dev...
CINDY 186: June 2009
http://ccesporlas-ap186.blogspot.com/2009_06_01_archive.html
Wednesday, June 17, 2009. Activity 1 Digital Scanning. Knowing the numerical values of a hand-drawn plot is a very tedious job when done manually. But with the help of technology and a bit of knowledge about image properties and a spreadsheet application, we can easily determine the numerical values of a hand-drawn plot. Figure1. Digitally scanned image of hand-drawn plot. Figure2. Produced plot from . Figure3. Produced digitally-scanned plot superimposed on the original plot image. I thank Mr. Gilbe...
CINDY 186: Activity 16 | Neural Networks
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Wednesday, September 9, 2009. Activity 16 Neural Networks. We have already investigated and implemented two methods for object classification using object features which are Minimum Euclidean Distance and Linear Discriminant Analysis. Another method that can be used for object classification is Neural Networks. This method imitates the way the human brain process information like a network of neurons thus the name Neural Networks. Figure 1. Neural Network Framework. In this activity we feed the obtained ...
CINDY 186: July 2009
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Monday, July 20, 2009. Activity 8 Morphological Operations. Morphological operations simply refers to operating on the structure of something and these operations can be thought of like operations on sets like 'union', 'intersection', 'complement' and many others. An example of operations is the XOR which is union minus intersection and [NOT(A)] AND B which is the intersection of 'complement of A' and 'B'. Figure 1. Structuring elements. Figure 2. Resulting images after dilation. Posted by cindy esporlas.
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Chocolate lover: July 2011
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Wednesday, July 13, 2011. Even if everybody thinks you're not. I still believe that you are". We are human beings. not perfect. but we shouldn't be deprived of the chance to improve ourselves and show the society the better side of us. Just some random thoughts from a very lazy evening. I remember the time when I last spoke about this. Subscribe to: Posts (Atom).
Chocolate lover: Happy weekend ^_^
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Friday, June 17, 2011. And so my day ended very happily! I know God will not let things happen without lessons to be learned. I will always trust in You Lord. What a happy weekend indeed! Subscribe to: Post Comments (Atom). I was just so scared.
Malese-ous: June 2009
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Monday, June 29, 2009. Activity 4 - Enhancement by Histogram Manipulation. Contrast is an important characteristic of images. It enables us to distinguish details. However, conditions may not be optimized to meet the desired contrast. It is often necessary to digitally process images to enhance its appearance. I rate this entry 10 for completing the activity and successfully backprojecting, which was the tricky part in my opinion. Xbasc();/ to clear image window. Old=trial(i);/ enhanced image. New=(old-d...
Pixel of Knowledge: lessons from drinking sessions..part 1.
http://otarun.blogspot.com/2010/10/lessons-from-drinking-sessionspart-1.html
On pics, physics, and more! Sunday, October 3, 2010. Lessons from drinking sessions.part 1. Nakausap ko si Fidel Rillo habang ako ay nakipag-inuman sa bahay ng aming kaibigan (tawagin natin Mambo) bilang despidida nya papuntang Germany. Nais kong ibahagi ang mga bagay na napagusapan namin. Tinanong ako ng "What is God? Isang sagot ang binigay sa akin ng tatay ng aking kaibigan. "it is the search for truth". It is the search for truth.science and God. Subscribe to: Post Comments (Atom).
Chocolate lover: Activity 18 Noise model and basic image restoration
http://jrvitug.blogspot.com/2009/10/activity-18-noise-model-and-basic-image.html
Saturday, October 10, 2009. Activity 18 Noise model and basic image restoration. In this activity, we try to demonstrate the different types of noise and image restoration techniques. Similar to image enhancement technique, this method aims to improve the quality of images surrounded with noise. However, this technique is more of object type as compared to image enhancement technique which is subjective in nature. Figure 1. Clean image and its PDF. Where z is the gray level value,. Is the average, and.
Malese-ous: July 2012
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Wednesday, July 25, 2012. So I've been away for a really long time.This was an academic blog turned personal blog turned I dunno. As of today, I've decided to use this blog for posting game dev related topics because, hey, I'm a game developer now! Who would have thought? Definitely not the past me. Anyway, I hope I get to keep my promise this time. This only serves as an intro, so nothing game dev related here yet. So there! Subscribe to: Posts (Atom).
Pixel of Knowledge: August 2009
http://otarun.blogspot.com/2009_08_01_archive.html
On pics, physics, and more! Thursday, August 6, 2009. Activity 12: Color Image Segmentation. Segmentation by thresholding will not always work especially when the area of interest has the same grayscale value as the background. In such cases, segmentation can be done using the color of the image of interest. In this activity, we're going to demonstrate parametric and non-parametric color segmentation. Normalize Chromaticity Coordinates (NCC). Can be obtained from r. Essentially, what this PDF does is to ...
Chocolate lover: July 2009
http://jrvitug.blogspot.com/2009_07_01_archive.html
Thursday, July 23, 2009. Enhancement in the Frequency Domain. Image enhancement is any digital process which aims to improve the quality of images by adjusting the contrast, brightness, sharpness, boundaries and edges [1]. One of the techniques used to enhance the visual qualities of images is by filtering out unwanted frequencies. This is done through the use of a mask. A mask is a small square window of values by which the current pixel and its neighbor are weighted to produce and output pixel [1].
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CINDY 186
Monday, October 5, 2009. Activity 18 Noise Models and Basic Image Restoration. Image restoration is a basic image processing application where an image that has been degraded or damaged is being recovered. To recover the image, the degradation must be known and thus can be used in restoring the image. Figure 1. PDFs of different noise types. Figure 2. Types of filtering used. Figure 3. Test image and its PDF. Figure 4 shows the noisy image for the added Gaussian noise with mean = 0.5 and standard dev...
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