tailieunhanh - Lecture Digital image processing - Lecture 27: Image segmentation

This chapter presents the following content: Image segmentation by thresholding, global threshold, adaptive/dynamic threshold, local threshold, segmentation algorithms, discontinuity based segmentation link the edge points. | Digital Image Processing CSC331 Image Segmentation 1 Summery of previous lecture Segmentation Algorithms Discontinuity based segmentation points, lines and edges Link the edge points Local processing Global processing (Hough transformation) 2 Todays lecture Image Segmentation by thresholding Global threshold Adaptive/Dynamic threshold Local threshold 3 Segmentation Algorithms Segmentation algorithms are based on one of two basic properties of color, gray values, or texture: Discontinuity Partition an image based on abrupt changes in intensity, Isolated points, lines and edges. Differences are sudden changes (discontinuities) in any of these, but especially sudden changes in intensity along a boundary line, which is called an edge. Similarity Partitioning an image into regions that are similar according to a predefined criteria. Thresholding, Region growing and region splitting and merging. Similarity may be due to pixel intensity, color or texture. Segmentation by thresholding Thresholding is the simplest method of image segmentation. The basic thresholding methods replace each pixel in an image with a black pixel if the image intensity is less than some fixed constant T, or a white pixel if the image intensity is greater than that constant. 5 6 7 How to get the intensity values ? The best way is by taking the histogram of the image. 8 9 Single threshold Multiple threshold Thresholding 11 Multilevel thresholding is possible (although more difficult in practice) Types of thresholds Global threshold Adaptive/Dynamic threshold Local threshold 12 13 Global threshold 14 Thresholding Basic Global Thresholding Selection of the value for T automatically 16 Thresholding Basic Global Thresholding 18 Global Thresholding issue Basic Adaptive Thresholding Divide original image into subimages Utilize a different threshold to segment each subimage If Difficulties: Subdivision and subsequent threshold estimation 20 Thresholding Basic Adaptive Thresholding (dividing the . | Digital Image Processing CSC331 Image Segmentation 1 Summery of previous lecture Segmentation Algorithms Discontinuity based segmentation points, lines and edges Link the edge points Local processing Global processing (Hough transformation) 2 Todays lecture Image Segmentation by thresholding Global threshold Adaptive/Dynamic threshold Local threshold 3 Segmentation Algorithms Segmentation algorithms are based on one of two basic properties of color, gray values, or texture: Discontinuity Partition an image based on abrupt changes in intensity, Isolated points, lines and edges. Differences are sudden changes (discontinuities) in any of these, but especially sudden changes in intensity along a boundary line, which is called an edge. Similarity Partitioning an image into regions that are similar according to a predefined criteria. Thresholding, Region growing and region splitting and merging. Similarity may be due to pixel intensity, color or texture. Segmentation by thresholding .