Chapter 4 SEGMENTATION

24 CHAPTER 4. SEGMENTATION(a)(b)Figure 4.12: (a) Output from Laplacian-of-Gaussian filter (σ 2 = 27) applied to muscle fibresimage. (b) Zero-crossings from (a) with average image gradients in excess of 1.0, in whitesuperimposed on the image.(σ 2 = 27), applied to the muscle fibres image. Boundaries corresponding to weak edges canbe suppressed by applying a threshold to the average gradient strength around a boundary.Fig 4.12(b) shows zero-crossings of the Laplacian-of-Gaussian filter with average gradients exceedingunity, superimposed on the original image. In this application the result can be seento be little better than simple thresholding.4.3 Region-based segmentationSegmentation may be regarded as spatial clustering:• clustering in the sense that pixels with similar values are grouped together, and• spatial in that pixels in the same category also form a single connected component.Clustering algorithms may be agglomerative, divisive or iterative (see, for example, Gordon,1981). Region-based methods can be similarly categorized into:• those which merge pixels,• those which split the image into regions, and