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Thursday, September 23, 2010. Playing Notes by Image Processing. The goal of this activity is to use image processing techniques to extract musical notes from a scanned music sheet and play it in Scilab. I used the music sheet for "Twinkle Twinkle Little Star" as shown in figure 1. The problem to answer is how to detect the types of notes and the pitch level. Now, let us go through the steps of the method used. :). Figure 1. Music sheet used in the activity. A Detection of the types of notes. In Scilab, ...

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tiny_meany | tinymeany.blogspot.com Reviews

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Thursday, September 23, 2010. Playing Notes by Image Processing. The goal of this activity is to use image processing techniques to extract musical notes from a scanned music sheet and play it in Scilab. I used the music sheet for Twinkle Twinkle Little Star as shown in figure 1. The problem to answer is how to detect the types of notes and the pitch level. Now, let us go through the steps of the method used. :). Figure 1. Music sheet used in the activity. A Detection of the types of notes. In Scilab, ...

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2 click this link

3 references

4 1 music sheet

5 2 frequencies

6 3 pitch levels

7 posted by

8 mean mean

9 3 comments

10 color image processing

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tiny_meany | tinymeany.blogspot.com Reviews

https://tinymeany.blogspot.com

Thursday, September 23, 2010. Playing Notes by Image Processing. The goal of this activity is to use image processing techniques to extract musical notes from a scanned music sheet and play it in Scilab. I used the music sheet for "Twinkle Twinkle Little Star" as shown in figure 1. The problem to answer is how to detect the types of notes and the pitch level. Now, let us go through the steps of the method used. :). Figure 1. Music sheet used in the activity. A Detection of the types of notes. In Scilab, ...

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tiny_meany: Binary Operations

http://tinymeany.blogspot.com/2010/09/binary-operations.html

Monday, September 20, 2010. Closing and opening operations are both derived from dilation and erosion. Closing is defined as. Dilation followed by an erosion using the same structuring element [1]. Opening on the other hand is closing in reverse. It is defined as erosion followed by dilation using the same structuring element [2]. In this activity, operations such as closing and opening will be applied to facilitate separation of region of interest (ROI) from the background in an image. Figure 5. Noi...

2

tiny_meany: June 2010

http://tinymeany.blogspot.com/2010_06_01_archive.html

Wednesday, June 30, 2010. Area Estimation for Images with Defined Edges. This fourth activity is about area measurement. Using Green's Theorem, the area of a defined contour can be obtained. Green's Theorem says that the line integral of the boundary is equal to the area enclosed within that boundary. Figure 1. Different shapes created using Paint. Rectangle: A = Length*Width (1). Square: A= Side*Side (2). Right triangle = (1/2)(Base*Height) (3). Table 1. Analytical areas of different shapes. Figure 5&#4...

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tiny_meany: July 2010

http://tinymeany.blogspot.com/2010_07_01_archive.html

Monday, July 19, 2010. Fourier Transform Model of Image Formation. Fourier Transform (FT) is a powerful tool in image processing. It gives the spatial frequency, that is, for a signal of dimension X, the FT gives 1/X. This activity is divided into four parts, so let us go through each part. A Familiarization of the discrete FFT. Figure 1.a Image of a 128x128 white circle with a black background. Notice that the result of the FFT looks like a black picture, but don't be fooled! Look closely at the edges!

4

tiny_meany: Color Image Segmentation

http://tinymeany.blogspot.com/2010/09/color-image-segmentation.html

Tuesday, September 21, 2010. Color image segmentation is very useful in separating parts of the images when the gray level values of the region of interest (ROI) is almost the same as the background. Figure 1 shows an image of a red bell pepper that will be used in this activity. The goal is to separate the red bell pepper from the background. Can it be done using thresholding of the gray level values? Let's see. :). In fact, there is. :). Figure 1. Image used to demonstrate color image segmentation.

5

tiny_meany: Enhancement in the Frequency Domain

http://tinymeany.blogspot.com/2010/08/enhancement-in-frequency-domain.html

Tuesday, August 10, 2010. Enhancement in the Frequency Domain. In paint, two dots symmetric along the x-axis were made and then loaded into Scilab. The FT was taken, as shown in figure 1. Figure 1. Two dots symmetric along the x-axis (left) and its FT (right). Figure 2. Dots with increased radius (left) and their corresponding FTs. Figure 3. Two squares of increasing width (left) and the corresponding. Figure 4. Two gaussians of varying variance (left) and the corresponding FT (right). Figure 9. Desi...

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Thursday, September 23, 2010. Playing Notes by Image Processing. The goal of this activity is to use image processing techniques to extract musical notes from a scanned music sheet and play it in Scilab. I used the music sheet for "Twinkle Twinkle Little Star" as shown in figure 1. The problem to answer is how to detect the types of notes and the pitch level. Now, let us go through the steps of the method used. :). Figure 1. Music sheet used in the activity. A Detection of the types of notes. In Scilab, ...

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