Sketch-based Image Retrieval on Mobile Devices Using Compact Hash Bits

• Main Authors: Kai-Yu Tseng, 曾開瑜
• Other Authors: Winston H. Hsu
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/86812733175523374451

碩士 === 國立臺灣大學 === 資訊網路與多媒體研究所 === 100 === With the advance of science and technology, touch panels in mobile devices has provided a good platform for mobile sketch search. Moreover, the request of real time application on mobile devices becomes increasingly urgent and most applications are based on large dataset so these dataset should be indexed for efficiency. However, most of previous sketch image retrieval system are usually provided on the server side and simply adopt an inverted index structure on image database, which is formidable to be operated in the limited memory of mobile devices independently. In this paper, we propose a novel approach to address these challenges. First, we effectively utilize distance transform (DT) features and their deformation formula to bridge the gap between manual sketches and natural images. Then these high-dimensional features are further projected to more compact binary hash bits, which can effectively reduce the memory usage and we will compare the performance with different sketch based image retrieval techniques. The experimental results show that our method achieves very competitive retrieval performance with other state of the arts approaches but only requires much less memory storage. Due to its low consumption of memory, the whole system can independently operate on the mobile devices.