9. Conclusion

In this chapter, a measurement method of photo aesthetics is presented. Several factors for measuring the beauty of a photo are discussed, including low-level features, photo semantics, image composition, and personal preference. Image composition plays an important role on the photo beauty measurement and a detection method is presented in this chapter. Object detection and image segmentation algorithms are aided to illustrate the layout of a photo and the social network helps finding the personal preference of a photo. Both the decision tree and MLP have high accuracy that is above 90% for evaluation. The decision tree can generate readable classification rules, while the MLP can give aesthetics scores to stand for the degree of beauty. The photo beauty measurement system can be implemented in real time, which is suitable for the installation of various kinds of equipment.
