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Search found 38 results on 2 pages for 'hsv'.

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  • Segmenting and masking all shades of red from an image using opencv

    - by vrinda
    I am trying to segment all shades of red form an image using hue saturation values and use InRangeS function to create a mask which should have all red areas whitened and all others blacked(a new 1 channel image). Thwn Inpaint them to kind of obscure the segmented portions. My code is as given. However I am unable to get an output image, it doesnt segment the desired color range. Any pointers on my approach and why it isnt working. ? using namespace std; int main() { IplImage *img1=cvLoadImage("/home/techrascal/projects/test1/image2.jpeg"); //IplImage *img3; IplImage *imghsv; IplImage *img4; CvSize sz=cvGetSize(img1); imghsv=cvCreateImage(sz,IPL_DEPTH_8U,3); img4=cvCreateImage(sz,IPL_DEPTH_8U,1); int width = img1->width; int height = img1->height; int bpp = img1->nChannels; cvNamedWindow("original", 1); cvNamedWindow("hsv",1); cvNamedWindow("Blurred",1); int r,g,b; // create inpaint mask: img 4 will behave as mask cvCvtColor(img1,imghsv,CV_BGR2HSV); CvScalar hsv_min = cvScalar(0, 0, 0, 0); CvScalar hsv_max = cvScalar(255, 0, 0, 0); //cvShowImage("hsv",imghsv); cvInRangeS( imghsv, hsv_min, hsv_max, img4 ); cvInpaint(img1, img4, img1, 3,CV_INPAINT_NS ); cvShowImage("Blurred",img1); cvReleaseImage(&img1); cvReleaseImage(&imghsv); cvReleaseImage(&img4); //cvReleaseImage(&img3); char d=cvWaitKey(10000); cvDestroyAllWindows(); return 0;}

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  • Remote Diagnostic Agent (RDA) version 4.30

    - by inowodwo
    posted by Maurice Bauhahn Remote Diagnostic Agent (RDA) version 4.30 was released on December 11th A free download can be accessed via Knowledge Management article 314422.1 and installed in any Enterprise Performance Management 11.1.2.x environment. EPM-specific instructions are available in Knowledge Management article 1304885.1. This RDA version incorporates two new modules (EAS=Essbase Administration Services; HWA=Hyperion Web Analysis) and improvements in modules and profiles relating to twelve other Hyperion applications (EPM, EPMA, ESS, FCM, HFM, HFR, HIR, HPL, HPSV, HSS, PR, and HSV). To follow best practice, run related RDA profiles [for example: "perl rda.pl -vnSCRPp Hyperion1112_EAS"] and attach the output zip file [by default in \rda\output\] to your service requests. The comprehensive set of details provided in such output files should help technicians to avoid delays in handling service requests (by avoiding ping-pong communications resulting from repeated requests for additional values).

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  • 2-components color model

    - by Cyan
    RGB is the natural color model for OpenGL. But a lot of other color models exist. For example, CMY(K) for printers, YUV for JPEG, the little cousins YCbCr and YCoCg, HSL & HSV from the 70's, and so on. All these models tend to share a common property : they are based on 3 components. Therefore my question is : Does it exist a 2-components color model ? I'm surprised to not find any. I was expecting something along the line of Hue+light could exist. I guess it cannot be as "complete" as a true 3-components color model, but a fine-enough approximation will be good for my usecase. The end objective is to store the 2 components into a single BC5 texture (GL_COMPRESSED_RED_GREEN_RGTC2 in OpenGL). The 3rd component requires a second fetch into a second texture, which hurts performance.

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  • Android horizontal scollview behave like iPhone (paging)

    - by Davide Vosti
    I have a LinearLayout inside a HorizontalScrollView. The content is just a image. While scrolling, I need to achieve the same behavior you get when setting the paging option on a the iPhone equivalent of the HSW (scrolling the list should stop at every page on the list, not continue moving). How is this done in Android? Should I implement this features by myself or there is a particular property to set or a subclass of HSV to implement? Thanks

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  • How to generate spectrum color palettes

    - by ddimitrov
    Is there an easy way to convert between color models in Java (RGB, HSV and Lab). Assuming RGB color model: How do I calculate black body spectrum color palette? I want to use it for a heatmap chart. How about single-wavelength spectrum? Edit: I found that the ColorSpace class can be used for conversions between RGB/CIE and many other color models.

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  • plot matrix missing points in different color using gnuplot

    - by kitt
    I have a file 'matrix.dat': 1 2 3 4 5 5 - 3 4 5 - 4 5 B - 1 B 2 B 3 - 3 2 - 3 I want to plot numbers using palette, '-' using white color and 'B' using black color. In gnuplot, I use this palette (blue - cyan - green - orange - red): set palette model HSV functions 0.666*(1-gray), 1, 1 And set '-' as missing data: set datafile missing "-" plot 'matrix.dat' matrix with image Now I can only plot numbers and '-' in correct colors.

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  • problem with hand tracking, opencv

    - by JP Talusan
    I am currently creating an opencv program that identifies a hand in an image and then gets the contour of the hand only, in order for us to get the center (x,y)m in pixels, of the hand. The problem is that whenever the image or video includes an arm or a face, we can't split or separate the hand from the contours of the arm or the face. We are currently using an HSV flesh colored histogram to get the contours of the hand. is there a way to separate them, i just need the hand. also if the picture includes only a hand and some part of the arm. How can we isolate the palm itself from the rest of the picture. all we need is a clear center of the palm. thanks in advanced.

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  • Opencv: Converting hue image to RGB image

    - by jhaip
    I am trying to show the hue component of the image from my webcam. I have split apart the image into the hue component but I can't figure out how to show the hue component as the pure colors. For example if one pixel of the image was B=189 G=60 R=60 then in HSV, H=0. I don't want the draw image to be the the gray values of hue but the RGB equivalent of the hue or H=0 - B=0 G=0 R=255 IplImage *image, *imageHSV, *imageHue; image = cvQueryFrame(capture); //image from webcam imageHSV = cvCreateImage( cvGetSize(image), IPL_DEPTH_8U, 3 ); imageHue = cvCreateImage( cvGetSize(image), IPL_DEPTH_8U, 1 ); cvCvtColor( image, imageHSV, CV_BGR2HSV ); cvSplit( imageHSV, imageHue, 0, 0, 0 ); I have a feeling there is a simple solution so any help is appreciated.

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  • C# Calling Methods in Generic Classes

    - by aip.cd.aish
    I am extending the ImageBox control from EmguCV. The control's Image property can be set to anything implementing the IImage interface. All of the following implement this interface: Image<Bgr, Byte> Image<Ycc, Byte> Image<Hsv, Byte> Now I want to call the Draw method on the object of the above type (what ever it may be). The problem is when I access the Image property, the return type is IImage. IImage does not implement the Draw method, but all of the above do. I believe I can cast the object of type IImage to one of the above (the right one) and I can access the Draw method. But how do I know what the right one is? If you have a better way of doing this, please suggest that as well.

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  • Drawing random smooth lines contained in a square [migrated]

    - by Doug Mercer
    I'm trying to write a matlab function that creates random, smooth trajectories in a square of finite side length. Here is my current attempt at such a procedure: function [] = drawroutes( SideLength, v, t) %DRAWROUTES Summary of this function goes here % Detailed explanation goes here %Some parameters intended to help help keep the particles in the box RandAccel=.01; ConservAccel=0; speedlimit=.1; G=10^(-8); % %Initialize Matrices Ax=zeros(v,10*t); Ay=Ax; vx=Ax; vy=Ax; x=Ax; y=Ax; sx=zeros(v,1); sy=zeros(v,1); % %Define initial position in square x(:,1)=SideLength*.15*ones(v,1)+(SideLength*.7)*rand(v,1); y(:,1)=SideLength*.15*ones(v,1)+(SideLength*.7)*rand(v,1); % for i=2:10*t %Measure minimum particle distance component wise from boundary %for each vehicle BorderGravX=[abs(SideLength*ones(v,1)-x(:,i-1)),abs(x(:,i-1))]'; BorderGravY=[abs(SideLength*ones(v,1)-y(:,i-1)),abs(y(:,i-1))]'; rx=min(BorderGravX)'; ry=min(BorderGravY)'; % %Set the sign of the repulsive force for k=1:v if x(k,i)<.5*SideLength sx(k)=1; else sx(k)=-1; end if y(k,i)<.5*SideLength sy(k)=1; else sy(k)=-1; end end % %Calculate Acceleration w/ random "nudge" and repulive force Ax(:,i)=ConservAccel*Ax(:,i-1)+RandAccel*(rand(v,1)-.5*ones(v,1))+sx*G./rx.^2; Ay(:,i)=ConservAccel*Ay(:,i-1)+RandAccel*(rand(v,1)-.5*ones(v,1))+sy*G./ry.^2; % %Ad hoc method of trying to slow down particles from jumping outside of %feasible region for h=1:v if abs(vx(h,i-1)+Ax(h,i))<speedlimit vx(h,i)=vx(h,i-1)+Ax(h,i); elseif (vx(h,i-1)+Ax(h,i))<-speedlimit vx(h,i)=-speedlimit; else vx(h,i)=speedlimit; end end for h=1:v if abs(vy(h,i-1)+Ay(h,i))<speedlimit vy(h,i)=vy(h,i-1)+Ay(h,i); elseif (vy(h,i-1)+Ay(h,i))<-speedlimit vy(h,i)=-speedlimit; else vy(h,i)=speedlimit; end end % %Update position x(:,i)=x(:,i-1)+(vx(:,i-1)+vx(:,i))/2; y(:,i)=y(:,i-1)+(vy(:,i-1)+vy(:,1))/2; % end %Plot position clf; hold on; axis([-100,SideLength+100,-100,SideLength+100]); cc=hsv(v); for j=1:v plot(x(j,1),y(j,1),'ko') plot(x(j,:),y(j,:),'color',cc(j,:)) end hold off; % end My original plan was to place particles within a square, and move them around by allowing their acceleration in the x and y direction to be governed by a uniformly distributed random variable. To keep the particles within the square, I tried to create a repulsive force that would push the particles away from the boundaries of the square. In practice, the particles tend to leave the desired "feasible" region after a relatively small number of time steps (say, 1000)." I'd love to hear your suggestions on either modifying my existing code or considering the problem from another perspective. When reading the code, please don't feel the need to get hung up on any of the ad hoc parameters at the very beginning of the script. They seem to help, but I don't believe any beside the "G" constant should truly be necessary to make this system work. Here is an example of the current output: Many of the vehicles have found their way outside of the desired square region, [0,400] X [0,400].

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  • Generate colors between red and green for a power meter?

    - by Simucal
    I'm writing a java game and I want to implement a power meter for how hard you are going to shoot something. I need to write a function that takes a int between 0 - 100, and based on how high that number is, it will return a color between Green (0 on the power scale) and Red (100 on the power scale). Similar to how volume controls work: What operation do I need to do on the Red, Green, and Blue components of a color to generate the colors between Green and Red? So, I could run say, getColor(80) and it will return an orangish color (its values in R, G, B) or getColor(10) which will return a more Green/Yellow rgb value. I know I need to increase components of the R, G, B values for a new color, but I don't know specifically what goes up or down as the colors shift from Green-Red. Progress: I ended up using HSV/HSB color space because I liked the gradiant better (no dark browns in the middle). The function I used was (in java): public Color getColor(double power) { double H = power * 0.4; // Hue (note 0.4 = Green, see huge chart below) double S = 0.9; // Saturation double B = 0.9; // Brightness return Color.getHSBColor((float)H, (float)S, (float)B); } Where "power" is a number between 0.0 and 1.0. 0.0 will return a bright red, 1.0 will return a bright green. Java Hue Chart: Thanks everyone for helping me with this!

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  • Good way to identify similar images?

    - by Nick
    I've developed a simple and fast algorithm in PHP to compare images for similarity. Its fast (~40 per second for 800x600 images) to hash and a unoptimised search algorithm can go through 3,000 images in 22 mins comparing each one against the others (3/sec). The basic overview is you get a image, rescale it to 8x8 and then convert those pixels for HSV. The Hue, Saturation and Value are then truncated to 4 bits and it becomes one big hex string. Comparing images basically walks along two strings, and then adds the differences it finds. If the total number is below 64 then its the same image. Different images are usually around 600 - 800. Below 20 and extremely similar. Are there any improvements upon this model I can use? I havent looked at how relevant the different components (hue, saturation and value) are to the comparison. Hue is probably quite important but the others? To speed up searches I could probably split the 4 bits from each part in half, and put the most significant bits first so if they fail the check then the lsb doesnt need to be checked at all. I dont know a efficient way to store bits like that yet still allow them to be searched and compared easily. I've been using a dataset of 3,000 photos (mostly unique) and there havent been any false positives. Its completely immune to resizes and fairly resistant to brightness and contrast changes.

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