信息隐藏与数字水印信息隐藏(Information Hiding and Digital Watermarking)

主要研究如何将某一机密信息秘密隐藏于另一公开的信息中，然后通过公开信息的传输来传递机密信息。对加密通信而言，可能的监测者或非法拦截者可通过截取密文，并对其进行破译，或将密文进行破坏后再发送，从而影响机密信息的安全；但对信息隐藏而言，可能的监测者或非法拦截者则难以从公开信息中判断机密信息是否存在，难以截获机密信息，从而能保证机密信息的安全。多媒体技术的广泛应用，为信息隐藏技术的发展提供了更加广阔的领域。由于数字水印是实现版权保护的有效办法，因此如今已成为多媒体信息安全研究领域的一个热点，也是信息隐藏技术研究领域的重要分支。该技术即是通过在原始数据中嵌入秘密信息–水印来证实该数据的所有权。这种被嵌入的水印可以是一段文字、标识、序列号等，而且这种水印通常是不可见或不可察的，它与原始数据 (如图象、音频、视频数据 )紧密结合并隐藏其中，并可以经历一些不破坏源数据使用价值或商用价值的操作而能保存下来。数字水印技术除了应具备信息隐藏技术的一般特点外，还有着其固有的特点和研究方法。在数字水印系统中，隐藏信息的丢失，即意味着版权信息的丢失，从而也就失去了版权保护的功能，也就是说，这一系统就是失败的。由此可见，数字水印技术必须具有较强的鲁棒性、安全性和透明性。

The dramatic development of multimedia and network techniques has made it much easier to generate, store, and transmit different types of media like image, video, and audio. However, content owners also see a high risk of piracy. In such background, digital watermarking techniques emerged as an effective way for multimedia protection. Digital watermarking technique is an interdisciplinary. Researchers with different backgrounds like communication, information theory, cryptography, image/video/audio processing etc congregated to this emerging hot field. Many related methods like spread-spectrum technique, independent component analysis, and principle component analysis etc are introduced. Digital watermarking techniques can be used to protect not only images, audio and video data, but also some unusual types of media.

音乐信息检索(Music Information Retrieval)

在迅猛增加的多媒体数据中，听觉信息占有总信息量的约20%左右，语音和音乐是最常见的声音媒体。而基于内容的音频检索是通过对音频数据的声学特征分析，如基频、幅度、共振峰结构、音调、响度和MFCC系数等声学特征。最简单的基于内容音频检索使用查询和存储的音频片段之间的样本到样本之间的比较。音乐信息检索MIR(Music Information Retrieval)目前是一个广义的概念，包括一切与数字音乐理解、分析相关的应用，如节拍估计、旋律提取、音频指纹、翻唱检索、和弦提取、打击乐/歌声检测及分离…..

The steep rise in music downloading over CD sales has created a major shift in the music industry away from physical media formats and towards online products and services. Music is one of the most popular types of online information and there are now hundreds of music streaming and download services operating on the World-Wide Web. Some of the music collections available are approaching the scale of ten million tracks and this has posed a major challenge for searching, retrieving, and organizing music content. Research efforts in music information retrieval have involved experts from music perception, cognition, musicology, engineering, and computer science engaged in truly interdisciplinary activity that has resulted in many proposed algorithmic and methodological solutions to music search using content-based methods. This paper outlines the problems of content-based music information retrieval and explores the state-of-the-art methods using audio cues (e.g., query by humming, audio fingerprinting, content-based music retrieval) and other cues (e.g., music notation and symbolic representation), and identifies some of the major challenges for the coming years.