Image Segmentation (Digital Image Processing)

Image Segmentation (Digital Image Processing)

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  Image Segmentation Subject: ImageProcesing & Computer Vision Dr. Varun Kumar Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 1 / 13
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  Outlines 1 What issegmentation ? 2 Different approach for image segmentation Discontinuity based Region based 3 Different edge detector operator 4 Linking of edge points Local processing Global processing 5 References Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 2 / 13
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  Image segmentation ⇒ Itis a process for dividing an image into its constituent part. Q At which level this division should be stopped. Ans Level of division is application dependent entity. Detection of movement measurement of vehicle on a road. Types of image segmentation 1 Discontinuity based approach: This approach is applicable, where there arise a abrupt changes in the intensity level in an image. Isolated points Lines present in an image Edges 2 Similarity based approach: Grouping of those pixels, which are similar in some sense. Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 3 / 13
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  Continued– Thresholding operation Region growingbased approach Region splitting and merging Discontinuity based approach Using suitable mask, we may be able for detecting Isolated points Lines present in an image Edges Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 4 / 13
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  Continued– R = 1 i=−1 1 j=−1 Wi,j f(x + i, y + j) 1 Point detection For point detection |R| > T where T is the given threshold. Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 5 / 13
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  Line detection 2 Linedetection Note: If |Ri | > |Rj | ∀ i = j then associated mask is more aligned towards the direction of ith mask. Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 6 / 13
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  Continued– 3 Edge detection Note:2nd order derivative is very sensitive to the noise→ not suitable for edge detection Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 7 / 13
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  Continued– Let f (x,y) is a image signal, where → f = Gx Gy = ∂f ∂x ∂f ∂y or f = mag(→ f ) = [Gx2 + Gy2 ]1/2 ≈ |Gx| + |Gy| Direction of → f α(x, y) = tan−1 Gy Gx Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 8 / 13
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  Continued– Previt edge operator Sobeledge operator Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 9 / 13
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  Results obtained dueto Sobel edge operator Results obtained due to Sobel edge operator Note: Previt and Sobel operators are the 1st order derivative operators. Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 10 / 13
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  Second derivative operator(Laplacian) 2 f = ∂2 f ∂x2 + ∂2 f ∂y2 Laplacian of Gaussian operator (LoG): h(x, y) = e− x2+y2 2σ2 Let x2 + y2 = r2 then 2 h = r2 − σ2 σ4 exp − r2 2σ2 Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 11 / 13
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  Continued– LoG and LoGmask Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 12 / 13
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  References M. Sonka, V.Hlavac, and R. Boyle, Image processing, analysis, and machine vision. Cengage Learning, 2014. D. A. Forsyth and J. Ponce, “A modern approach,” Computer vision: a modern approach, vol. 17, pp. 21–48, 2003. L. Shapiro and G. Stockman, “Computer vision prentice hall,” Inc., New Jersey, 2001. R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital image processing using MATLAB. Pearson Education India, 2004. Subject: Image Procesing & Computer Vision Dr. Varun Kumar (IIIT Surat)Lecture 26 13 / 13