Eng gt

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Eng gt

  1. 1. A Study on Classifying the Face Image s1180023 Kentaro Sekine Supervised by Prof. Qiangfu Zhao System Intelligence Laboratory 1
  2. 2. Outline  Introduction  Method  Result  Discussion 2
  3. 3. Introduction  It classify face images using k-means.  It performs some process to many images, and classifies into three classes using the k-means.  It performs morphing using the image of each class. image1 image2 middle image 3
  4. 4. Method The file of 200 image data is selected and loaded. 2. The image is normalized, and it converts it to the gray and mosaic. 3. Each image is converts to the feature vector. 4. It classifies these feature vectors into three classes using k-means. 1. 4
  5. 5. Method (Cont.) 5. It sorts it in ascending order for each class. 6. In experiment 1, it performs morphing two images difference in luminance value in each class. 7. In experiment 2, it chooses one image from each class, and performs morphing two images. 5
  6. 6. Result – Experiment 1 Processing time : 3.5[s] These three images are the face image made most throughout the experiment. We repeated many times the experiment, however, the result was alomost these three images. 6
  7. 7. Result – Experiment 2 Processing time : 3.5[s] It is an unnatural image because there are images made by the image that does not look like. It made several images others, however, these three images were more unnatural images. 7
  8. 8. Discussion  In experiment 1, it made a natural face image as a whole. Since the result is not changed even though repeating the experiment, the result is stable even with the k-means method.  Image made of experiment 2 was a very unnatural image because contour of the face was not match and there was a shadow. 8

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