Street Image Retouching Based on Image Mining

• Main Authors: LIN,JHIH-YU, 林芷羽
• Other Authors: 陳履恒
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/17240768961830450127

碩士 === 國立暨南國際大學 === 資訊工程學系 === 104 === With the advanced science and technology, we can use various mobile devices to get the latest information. In recent years, there are several research results of Route Recommendation developed and used in map navigation applications. For example, Google Map, a world-widely used online map service, provides 2D street map, satellite imagery, topographic map and street view navigation. The street view function is the most well-known one. Google Map also provides street view navigation service with scenery images. However, those scenes are unchangeable, static, and regardless of time, weather, and seasons. It is often hard for users to imagine the route scenes in reality. Therefore, in this research, we aim to develop an image retouching system for street scenes. By combining the Open Weather Map and the technology of Context Awareness, our system can obtain user’s geolocation and weather information. Based on this information, our system calculates the color clues which is related to the climate and weather conditions. This goal is achieved by utilizing image mining methods for extracting Flickr’s images and analyzing pictures’ color histograms. Then, our system performs image retouching to the pictures collected from Google Map’s street view. As the experiment results shown, the retouched scenes can present the users’ feelings and the weather influence. It can also provide a much more real experience of street view. Furthermore, after adding the Non-Photorealistic Rendering effects, users can enjoy a more vivid and interesting animation of street view.