题名 | 网络特定图像的分析与过滤 |
作者 | 杨金锋 |
学位类别 | 工学博士 |
答辩日期 | 2005-04-25 |
授予单位 | 中国科学院研究生院 |
授予地点 | 中国科学院自动化研究所 |
导师 | 谭铁牛 |
关键词 | 互联网络 信息过滤 肤色检测 图像识别 Internet Information ?ltering Skin detection Image recognition |
其他题名 | Analysis and Filtering of Speci?c Image onthe Internet |
学位专业 | 模式识别与智能系统 |
中文摘要 | 互联网络是当今社会信息传递的主要载体之一,也已社会发达程度的一个重要标志,它不仅扩展了人们的活动空间,而且创造了人们之间联系的新纽带,并已渗透到社会活动的各个领域,对社会的发展产生了革命性的影响。理性的人们在享受互联网络带来的丰硕成果时,也发现它对社会带来的危害,尤其是有害信息的广泛传播对未成年人造成的影响日益引起人们的广泛关注,成为迫切需要解决的关键问题。本文关注的焦点主要集中在两个方面:1)基于图像内容的网络过滤系统的设计;2)网络特定图像的分析和研究。本文主要的工作和贡献包括:1°设 计 了 一 个 合 理 的 基 于 客 户 端 的 网 络 有 害 信 息 过 滤 系 统 , 实 现 了 对 网 络 信息“堵”、“滤”结合的过滤模式,满足了实时过滤的基本需求。2°提出了一种改进的Gamma矫正方法。这种方法能根据像素本身的数值选择与其相关的Gamma数值,从而实现了对图像进行自适应矫正的目的,有效的弱化了光照对图像质量的影响。3° 深入研究了皮肤色彩的基本属性。提出了一个描述色彩通道之间关系的非线性变换,并在大规模统计的基础上,利用直方图呈现了“肤色”和“非肤色”这两类色彩的分布。用一个分段连续且闭合的曲线描述了肤色像素的分布区域,结合对肤色与非肤色像素重叠区域的分析,建立了一个非线性的肤色分类器。4° 深入研究了敏感图像识别中的有关问题。提出了一个快速有效的识别算法,算法从对图像的几何区域划分、区域生长、感兴趣区域提取、目标轮廓提取、局部信息检测、稳定性特征提取和识别等八个紧凑关联的环节完成了对图像属性的描述和性质判断。5° 提出了基于自适应网络的肤色区域轮廓构建算法。算法能够综合利用图像局部区域上的肤色和纹理信息快速确定多个目标区域并形成初始的目标轮廓,然后在引入虚拟引力场基础上,利用最小作用能原理完成了对初始轮廓的优化。总的说来,本文针对网络信息过滤问题,从系统实现、肤色检测、图像特征分析和目标轮廓构建等方面作了有益的探索。 |
英文摘要 | The main works of this paper are as follows. 1、 Developed Chinese Speech Recognition (CSR) system with phoneme as the base model, based on detailed study of our CSR technologies. Importance of Chinese tones information was showed from two aspects of speech recognition, such as feature and model. 2、 Characteristics of English were intensive studied first, and then our English Speech Recognition (ESR) system was developed, including initial model training and design of question set and decision tree based triphone model training and search process of the recognizer. Then semi-tied covariance modeling techniques are improved using more robust Bayes information as the criterior of deciding the number of covariance transformation matrix. The compensation in the log-spectral domain is also investigated to gain more robust acoustic model. At last, nonnative speaker adaptation was tested by data driven maximum likelihood linear regression (MLLR) fast adaptation algorithm. 3、 Japanese Speech Recognition (JSR) system was developed rapidly with fast bootstrapping method of MSR. Then end-point detection algorithm based on statistics is suggested. This algorithm is more robust for noisy speech than others. At last, simple tests of cross-language speech recognition from Chinese and English and Chinese-English bilingual system to Japanese were carried out. The results showed that bilingual acoustic model performed better than language-dependent models. 4、 Several Chinese-English bilingual acoustic modeling techniques were explored intensively, such as direct combination of two sets of base model and IPA mapping and automatic agglomerative clustering by different distance measures, e.g., Bhattacharyya distance, log-likelihood and maximum mutual information (MMI). Language related questions were adopted in the decision tree training process and achieved higher performance than the traditional method. |
语种 | 中文 |
其他标识符 | 200118014604895 |
内容类型 | 学位论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/5849] ![]() |
专题 | 毕业生_博士学位论文 |
推荐引用方式 GB/T 7714 | 杨金锋. 网络特定图像的分析与过滤[D]. 中国科学院自动化研究所. 中国科学院研究生院. 2005. |
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