tailieunhanh - Lecture Digital image processing - Lecture 29: Morphological image processing

This chapter presents the following content: Morphological image processing, set points, structuring elements, morphological operations, dilation and erosion, similarity base image segmentation, region-based segmentation, color based segmentation. | Digital Image Processing CSC331 Morphological image processing 1 Summery of previous lecture Similarity base Image Segmentation Region-based segmentation: region growing and region splitting and merging Color based segmentation 2 Todays lecture Morphological image processing Set points Structuring Elements Morphological operations Dilation and Erosion 3 4 Introduction Morphology: a branch of biology that deals with the form and structure of animals and plants Morphological image processing is used to extract image components for representation and description of region shape, such as boundaries, skeletons, and the convex hull Morphological Image Processing The field of mathematical morphology contributes a wide range of operators to image processing, all based around a few simple mathematical concepts from set theory. The operators are particularly useful for the analysis of binary images and common usages include edge detection, noise removal, image enhancement and image segmentation. structuring element Morphological techniques typically probe an image with a small shape or template known as a structuring element. The structuring element is positioned at all possible locations in the image and it is compared with the corresponding neighborhood of pixels. Morphological operations differ in how they carry out this comparison. 6 Set points 7 Fundamental Definitions We defined an image as an (amplitude) function of two, real (coordinate) variables a(x,y) or two, discrete variables a[m,n]. An alternative definition of an image can be based on the notion that an image consists of a set (or collection) of either continuous or discrete coordinates. In a sense the set corresponds to the points or pixels that belong to the objects in the image. This is illustrated in Figure which contains two objects or sets A and B. Note that the coordinate system is required. For the moment we will consider the pixel values to be binary. Figure : A binary image containing two object sets | Digital Image Processing CSC331 Morphological image processing 1 Summery of previous lecture Similarity base Image Segmentation Region-based segmentation: region growing and region splitting and merging Color based segmentation 2 Todays lecture Morphological image processing Set points Structuring Elements Morphological operations Dilation and Erosion 3 4 Introduction Morphology: a branch of biology that deals with the form and structure of animals and plants Morphological image processing is used to extract image components for representation and description of region shape, such as boundaries, skeletons, and the convex hull Morphological Image Processing The field of mathematical morphology contributes a wide range of operators to image processing, all based around a few simple mathematical concepts from set theory. The operators are particularly useful for the analysis of binary images and common usages include edge detection, noise removal, image enhancement and image .