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Wednesday, September 30, 2009. THIS IN THEORY IS THE LAST POST IN THIS BLOG! Activity 19: Restoration of Blurred Images. To demonstrate the concept of motion blur and its restoration as well as basic noise filtering. Scilab with SIP toolbox. We begin with an ordinary image with text written on it, in this case we use a grayscale image of the Apollo 13 Mission Patch with the words "Apollo XIII" and "Ex Luna Scientia.". We are in theory to simulate motion blur using the equation:. As usual Mr. Cabello ...

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ap186 ni raffy | ap186niraffy.blogspot.com Reviews

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Wednesday, September 30, 2009. THIS IN THEORY IS THE LAST POST IN THIS BLOG! Activity 19: Restoration of Blurred Images. To demonstrate the concept of motion blur and its restoration as well as basic noise filtering. Scilab with SIP toolbox. We begin with an ordinary image with text written on it, in this case we use a grayscale image of the Apollo 13 Mission Patch with the words Apollo XIII and Ex Luna Scientia.. We are in theory to simulate motion blur using the equation:. As usual Mr. Cabello ...

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ap186 ni raffy | ap186niraffy.blogspot.com Reviews

https://ap186niraffy.blogspot.com

Wednesday, September 30, 2009. THIS IN THEORY IS THE LAST POST IN THIS BLOG! Activity 19: Restoration of Blurred Images. To demonstrate the concept of motion blur and its restoration as well as basic noise filtering. Scilab with SIP toolbox. We begin with an ordinary image with text written on it, in this case we use a grayscale image of the Apollo 13 Mission Patch with the words "Apollo XIII" and "Ex Luna Scientia.". We are in theory to simulate motion blur using the equation:. As usual Mr. Cabello ...

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ap186niraffy.blogspot.com

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ap186 ni raffy: Activity 11: Color Camera Processing

http://www.ap186niraffy.blogspot.com/2009/08/activity-11-color-camera-processing.html

Friday, August 7, 2009. Activity 11: Color Camera Processing. To demonstrate the principle of color balancing in color cameras especially the post recording correction of improperly color balanced images. Scilab with SIP toolbox. We begin with several improperly color balanced images with several objects of different colors present. These have their color balance settings varied to show the effects of white balancing. August 10, 2009 at 5:25 PM. Subscribe to: Post Comments (Atom). View my complete profile.

2

ap186 ni raffy: Activity 17: Photometric Stereo

http://www.ap186niraffy.blogspot.com/2009/09/activity-17-photometric-stereo.html

Wednesday, September 9, 2009. Activity 17: Photometric Stereo. To reconstruct a three dimensional image using a set of 2-D images with different illumination positions. We start with four images of a spherical calibration target illuminated by a point source at these locations:. S1 = (0.085832, 0.17365, 0.98106). S2 = (0.085832, -0.17365, 0.98106). S3 = (0.17365, 0, 0.98481). S4 = (0.16318, -0.34202, 0.92542). Where g is given by:. For the proper reconstruction of the shape, a grade of 10 is appropriate.

3

ap186 ni raffy: August 2009

http://www.ap186niraffy.blogspot.com/2009_08_01_archive.html

Wednesday, August 26, 2009. Activity 14: Pattern Recognition. To demonstrate the application of pattern recognition in describing a set or ensemble of objects in an image. Scilab with SIP, an assembly of items with differnt shapes and sizes. Using the same processing scheme as with the training set sans the averaging segment, we find our two classification parameters from the image and plot this with the x-axis being the area and the y-axis representing the color values of the red-channel. Using linear a...

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ap186 ni raffy: Activity 13: Correcting Geometric Distortion

http://www.ap186niraffy.blogspot.com/2009/08/activity-13-correcting-geometric.html

Wednesday, August 26, 2009. Activity 13: Correcting Geometric Distortion. To demonstrate the process of correcting geometric distortions present in images. In order to simplify the computation, we use a grid of horizontal and vertical lines with barrel distortion present like the one we have below:. Now using the least distorted part of the test grid image, we compute c1 through c8 using the following matrices:. And then using the nearest neighbor interpolation we get:. Subscribe to: Post Comments (Atom).

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ap186 ni raffy: Activity 16: Neural Networks

http://www.ap186niraffy.blogspot.com/2009/09/activity-16-neural-networks.html

Wednesday, September 9, 2009. Activity 16: Neural Networks. To demonstrate the application of neural networks in pattern recognition. Scilab with SIP and ANN toolboxes. For this set, we classify this, in a manner similar to Boolean, as. That is to say, for our purposes, the last three sets, with the corresponding parameters are the ones to be classified under a certain heading and all the others effectively discarded. Now we define a test set of object parameters we wish to classify:.

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winsomerara.blogspot.com

Wanna Eat Six Kamatis: June 2009

http://winsomerara.blogspot.com/2009_06_01_archive.html

Wanna Eat Six Kamatis. Monday, June 29, 2009. ACTIVITY 2 Area Estimation for Images with Defined Edges. Length = (192-57) 1. Width = (145-55) 1. Area = Length x Width = 136 x 91 = 12376. Arrow, circle, heart, triangle, letter T, rectangle, trapezoid. Figure 2. This was done using Paint, zoomed to 800%. If it is already the last coordinate, then it must be multiplied to first coordinate to be able to close the contour line, a requirement for Green's theorem. 2 binarized image = im2bw(image,0.5);. I would ...

winsomerara.blogspot.com

Wanna Eat Six Kamatis: ACTIVITY 19 Restoration of Blurred Image

http://winsomerara.blogspot.com/2009/10/activity-19-restoration-of-blurred.html

Wanna Eat Six Kamatis. Monday, October 12, 2009. ACTIVITY 19 Restoration of Blurred Image. The following are the investigations I did in relation to the degradation and restoration of the image shown in Figure 1. 1) The value of T in H (degradation function, equation 2) was varied. 2) The values of a and b (same value) were varied. 3) The values of a and b (different values) were varied. 4) The standard deviation and mean in the Gaussian noise were varied. 4) The value of K in equation 4 was varied.

winsomerara.blogspot.com

Wanna Eat Six Kamatis: October 2009

http://winsomerara.blogspot.com/2009_10_01_archive.html

Wanna Eat Six Kamatis. Monday, October 12, 2009. ACTIVITY 19 Restoration of Blurred Image. The following are the investigations I did in relation to the degradation and restoration of the image shown in Figure 1. 1) The value of T in H (degradation function, equation 2) was varied. 2) The values of a and b (same value) were varied. 3) The values of a and b (different values) were varied. 4) The standard deviation and mean in the Gaussian noise were varied. 4) The value of K in equation 4 was varied.

winsomerara.blogspot.com

Wanna Eat Six Kamatis: August 2009

http://winsomerara.blogspot.com/2009_08_01_archive.html

Wanna Eat Six Kamatis. Thursday, August 6, 2009. ACTIVITY 12 Color Image Segmentation. Need not be shown here because its value can already be derived from r. Parametric segmentation is done by assuming that the probability distribution function (PDF) of the image is a Gaussian distribution independent along r. The Gaussian PDF equations, form shown in the manual, for r. Are established by getting the mean, standard deviation and variance of the rg. Values is used. The histogram is a N. Values. The n...

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ap1821 (Aivis) - DeviantArt

Window.devicePixelRatio*screen.width 'x' window.devicePixelRatio*screen.height) :(screen.width 'x' screen.height) " class="mi". Window.devicePixelRatio*screen.width 'x' window.devicePixelRatio*screen.height) :(screen.width 'x' screen.height) ". Join DeviantArt for FREE. Forgot Password or Username? Deviant for 4 Years. This deviant's full pageview. Last Visit: 70 weeks ago. This is the place where you can personalize your profile! By moving, adding and personalizing widgets. Why," you ask? May 16, 2011.

ap186-msison.blogspot.com

miguel AP 186 blog

Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

ap186-ni-moy.blogspot.com

ap186 blog ni momoy...

Ap186 blog ni momoy. Get h1n1 online ;p . reading entries = getting "the virus" for free :D. Monday, October 12, 2009. Activity 19: Restoration of Blurred Image. In this activity, we will apply Weiner filtering to restore an image of known degradation (in this case, blur) and additive noise. The process we followed for this activity is shown below:. In the Fourier space, this can be written as. To restore the image, we use the Weiner filter given below:. Where K is a specified constant. In this activity,...

ap186.blogspot.com

Applied Physics 186

Friday, October 14, 2011. This last experiment is about image processing using the frames of a video-captured scene. Videos are merely a string of still images captured at a certain frequency. This of course is still ruled by the Nyquist criterion to ensure a non-aliased signal (the video itself) in the perception of our eyes. This frequency is more known as the frame rate. Our selected time frame consisted of 14 still images. Figure 1. Sample of a still frame from our video. Finally, these 14 images wer...

ap186niraffy.blogspot.com

ap186 ni raffy

Wednesday, September 30, 2009. THIS IN THEORY IS THE LAST POST IN THIS BLOG! Activity 19: Restoration of Blurred Images. To demonstrate the concept of motion blur and its restoration as well as basic noise filtering. Scilab with SIP toolbox. We begin with an ordinary image with text written on it, in this case we use a grayscale image of the Apollo 13 Mission Patch with the words "Apollo XIII" and "Ex Luna Scientia.". We are in theory to simulate motion blur using the equation:. As usual Mr. Cabello ...

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Acción Promocional 18 de Julio

Desde el año 1983 está abocada a la Atención Primaria en Salud y cuenta con atención pediátrica, ginecológica, general, psicológica, psiquiátrica, vacunaciones y planificación familiar. Centro Juvenil Integral Ombú : Proyecto en convenio con INAU, Instituto de la Niñez y Adolescencia del Uruguay. En el Establecimiento, El Coraje al noreste del Departamento de Canelones, en la localidad de Tala, paraje rural Las Piedritas , se desarrollan actividades desde hace más de 20 años.

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װƷĲ Ҳ177װƷĹ�ѵȽǩ 5ڵ ձפδԱ仯. ϾΪͶӹԱ ѵʱڲĲ1228յ籾ڽൺʯݾеCBA22ൺΫ󱱾ũеıǰ2СʱͻȻӵڵ ݳ ȷȫ. ŽվڶййϿսԶ ݣձ 循šй ЩѵҲеġ. Ƶ1228յ硰ԼһһĿ飡1231գĿͽӭ 죬ϵϺڡǡݡɳ ɽؽ һʢ λ ҲΪչʾĻƷƵҪƽ. Ǿ쵼ɲ λԽߡλԽҪԽҪ Ͻ ලڼලûнû ǿڼලҪίԱξίԱξ ǵڼල쵼ߺƶߣҲǵڼලźͱ ߣȫźţȫΪߡίԱξ Ҫϰڼල չԾϿҽȫලҼලίԱξ ҪԾ ලȺڼලۼල. ΚƽǿξҪڿչΪȫʣҸսʿҪʵǣȡ ʱ Ҫã رǶϼҲҪá ԽԽ ááҪááùúãʹ ΪһϰߡһԾһΡ. 15սװսѵ 磩ýƣ ĸ θ ƽչԶѵ 26ձʾ5ս 嶫Ϸʶ20 Լ37 ʿϿУ úձȫ 䡣. ϾΪͶӹԱ ѵʱڲĲ1228յ籾ڽൺʯݾеCBA22ൺΫ󱱾ũеıǰ2СʱͻȻӵڵ ݳ ȷȫ. 183; ý ƻһ. 183; ȵô ߺ СҪ�ɱ. 183; ý ϵͳй"ĸɱ"-21D. 183; ɫк ͻ ſ. 183; ʮѲӹ 5. 183; ϽꪹƱ ļƷ. 183; 7ʤƿ ɨ. 183; ýȥ24СʱӺں 311ͼ-154ɻƬ. 183; Ѫ...