照相手机的流行及其具有的随身携带性，使得人们能够随时随地进行拍照。相比传统的相机来说，手机的联网性使得人们能够实时地进行图片搜索和分享。由此而来的手机图片数量的急剧增长，又使得如何高效地组织、管理以及检索这些图片成为了研究热点。为了高效地进行手机图片搜索，提出了一种融合相机元信息（Exif）的基于区域的手机图片搜索算法，同时利用这个算法实现了一个在线的用户手机拍摄图片的搜索系统。通过与传统的基于内容的手机图片搜索的对比可见，该算法通过融合进相机元信息以及物体的区域特征，在一定程度上降低了“语义鸿沟”问题。实验结果表明，该算法优于传统的基于底层特征的图片搜索算法。

The convenient attribute of cameraphone makes it popular nowadays: people can use it to snap picture at any time and everywhere. At the same time with the advantage of inherent network connectivity, we can share the snapped image with others immediately or search for similar images from the web. The above advantages of cameraphone make the quantity of cameraphone images boosting quickly, which results in the problem of how to efficient organize, manage and retrieve. In this paper, a new region based cameraphone images retrieval incorporated with metadata method is proposed to improve the image retrieval performance. Using this algorithm, we implemented an online demo system to allow users to upload their snapped images and do searching similar images. Compared to traditional contented based image retrieval (CBIR) method, ourmethod uses the region feature of the image incorporated withmetadata of cameraphone to bridge the semantic gap between the low-level feature of images and semantics. The experimental results show higher efficiency ofour methods than the traditional CBIR method.