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otarun.blogspot.com

Pixel of Knowledge: August 2009

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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 ...

otarun.blogspot.com

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).

otarun.blogspot.com

Pixel of Knowledge: July 2009

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On pics, physics, and more! Thursday, July 23, 2009. Activity 8: Morphological Operations. In this activity, we're going to demonstrate two basic morphological operations, dilation and erosion. We proceed by defining dilation and erosion using set theory and provide examples using different images. To futher understand dilation and erosion better, the reader is recommended to predict the outcome of dilation and erosion on a piece of paper before programming it on a computer. From our activity manual, "Th...

ap186-msison.blogspot.com

miguel AP 186 blog: Activity 16 Neural Networks

http://ap186-msison.blogspot.com/2009/09/activity-16-neural-networks.html

Miguel AP 186 blog. Wednesday, September 9, 2009. Activity 16 Neural Networks. Do you remember when I said machines are stupid? Table 1. Classification result and percent accuracy at different learning rates. Figure 1. Classification accuracy versus Neural Network learning rate. Red line highlights range with 100% accuracy. Maricor Soriano, A16 – Neural Networks, AP186 2008. Cole’s AP186 Blog. Subscribe to: Post Comments (Atom). There was an error in this gadget. Activity 17 Photometric Stereo.

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miguel AP 186 blog: Activity 15 Probabilistic Classification

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Miguel AP 186 blog. Wednesday, September 9, 2009. Activity 15 Probabilistic Classification. LDA calculates the probability, fij, of an object to belong in a class according to the equation. In this equation wi is the feature vector of object i and mj is the mean feature vector of class j. The value pj is the probability or ratio of the number of elements in class j over the total population of the classes. Table 1. Resulting probability of each object per class and classification results. Activity 15 Pro...

ap186-msison.blogspot.com

miguel AP 186 blog: August 2009

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Miguel AP 186 blog. Thursday, August 6, 2009. Activity 12 Color Image Segmentation. Figure 1. Normalize Chromaticity Coordinates. The normalized chromaticity coordinates (NCC), shown in figure 1, can be thought of as a way of expressing 3 dimensional RGB information to a simpler 2 Dimensional r-g color space. The basis for this transform is that r g b=1 (done by normalizing RGB), hence the third value is redundant and it is enough to express color by only two values, in this case r and g. Overall, by loo...

malese-ous.blogspot.com

Malese-ous: ACTIVITY 17 - Stereometry

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Monday, September 14, 2009. ACTIVITY 17 - Stereometry. The easiest case to work with would be a point source of light. The intensity would depend as 1/r 2, where r is the distance from the point source. The mathematical derivations will not be. Shown here. Just note that we need information on the different positions of the light source relative to the object and the following images. After applying some matrix operations, we obtain the following reconstruction. Figure 2. Reconstruction.

thejaggernaut.blogspot.com

Master's Piece: August 2009

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Reports, reports, reports. Friday, August 7, 2009. Activity 10: Preprocessing Text. In this activity, we are asked to extract information from a scanned document (figure 1) specifically handwriting. This activity is the integration of the techniques learned from the previous activities. The first task at hand is to clean the image by removing the horizontal and vertical lines present. Here we used filtering just like in activity 7. For this part only a portion of the image is used. Scilab crashes in Wind...