人工智能与模式识别的发展.ppt

* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * + Compare cash T account in Problem P3-6 with Net Income + Why is Cash Flow ° Net Income? + Why is Retained Earnings ° Cash? * * * * * * * * * * * Color Image Segmentation - Experiment 2 Hue Distinguishable (b) Intensity image * * Color Image Segmentation - Experiment 2 Hue Distinguishable (c) Hue image * * Color Image Segmentation - Experiment 2 Hue Distinguishable (d) Segmentation by intensity * * Color Image Segmentation - Experiment 2 Hue Distinguishable (e) Segmentation by hue and intensity * * Some More Illustrative Examplesof Medical Imaging Results * * * * * * * * * * * * * * * * * * * * * * PR (Pattern Recognition) andAI (Artificial Intelligence) * * * * * * * * * * * * * * * * Linear Combination Recognition: An unknown object is matched with a model by comparing the points in an image of the unknown object with a template-like collection of points produced from the model * * * * * * * * * * Experitment-1——Match same objects * * Experiment-1 Result * * Experiment-2 * * Experiment-3 … * * Experiment-3 Result * * Experiment-4 * * Experiment-4 Result Rejected Rejected Too * * * * * * * * * * Color Biometric Imaging Analysis * * Items to be discussed: Clustering and K-means algorithm Statistical Unsupervised Color Representation and Color Image Segmentation * * Supervised Classification and minimum distance classification Minimum Distance Classification Supervised Find the center of known patterns of each class Classify unknown patterns into the class that is “closest” to it. * * Color Image Segmentation: Hue Component * * Color Image Segmentation Task: Study the K-means algorithm in hue space. Interesting: Periodical Circular Property of hue component new Measure of Distance. Problem: K-means algorithm is based on the measure of distance and definition of center * * Hue Component Clustering Definition 1: Distance of Hue Values Defini