搜索资源列表
CBIR
- 本源码是用C++编写的基于内容的图像检索，采用形状、颜色、纹理三个特征的加权值作为特征向量。-The source code is written in c++ of content-based image retrieval, the shape, color, texture three characteristics of the weighted value as the characteristic vector.
CBIR
- Content Based Image Retrieval
1
- 状是含有高层语义信息的视觉特征，在基于内容的图像检索及图像识别中具有重要的应用价值。有很多种描述子可以描述图像的形状特征，傅立叶描述子可以把二维的图像轮廓信息简化成一维问题进行处理，应用非常广泛。然而自然图像的形状特征通常是杂乱的，有噪声的，提出了一种图像预处理方法，得到净化的形状图像，通过实验研究傅立叶描述子算法提取形状特征的效果。-Abstract Shape is a visual feature which contains intrinsic high-level semantics
shape
- CBIR with Shape method, very good
NSCT
- 1．分析研究了基于内容的图像检索系统的工作原理，关键技术如：纹 理、形状等图像底层特征的描述方法， 图像间的相似性度量方法， 图像库索引机制等。 2．研究了基于纹理特征的图像检索方法，并提出了一种基于NSCT 变 换的纹理特征提取方法。通过对SAR 图像及相关图像进行NSCT 分解，计算不同尺度不同方向上的系数幅度序列的均值，标准方差 和三阶中心矩，以此构成特征向量来描述图像的纹理。实验证明本 文提出的采用NSCT 算法有较好的特征提取效果，引入三阶中心矩 作为特
FEATURES
- 3 files: imageslicer for splitting RGB image to 8 bit plans, getTopology to extract topology features features, and getShape to extract shape features . (good features for CBIR systems)
CBIR-FOR-ENDOSCOPIC-IMAGES
- Content-based medical image retrieval is now getting more and more attention in the world, a feasible and efficient retrieving algorithm for clinical endoscopic images is urgently required. Methods: Based on the study of single feature image retr
CBIR-document
- CBIR is retrieval of images based on some query or example images. It is also called Query based image retrieval. Firstly, this report outlines a descr iption of the primitive features of an image color and shape. These features are extracted and use
fuliye
- 傅立叶描述子是分析和识别物体形状的重要方法之一．利用基于曲线多边形近似的连续傅立叶变换方法 计算傅立叶描述子，并通过形状的主方向消除边界起始点相位影响的方法，定义了新的具有旋转、平移和尺度不变 性的归一化傅立叶描述子．与使用离散傅立叶变换和模归一化的传统傅立叶描述子相比，新的归一化傅立叶描述 子同时保留了模与相位特性，因此能够更好地识别物体的形状．实验表明这种新的归一化傅立叶描述子比传统的 傅立叶描述子能够更加高效、准确地识别物体的形状．-Abstract Shape is a visual f
zhifangtujiansuo
- 基于内容的图像检索（Content-based Image Retrieval，简称CBIR）技术被提出。这一技术的出现提高了图像检索的准确性，它通过提取图像本身的内在客观特征如颜色、纹理、形状、布局等关系，并比较这些视觉特征间的相似性，自动搜索出符合用户要求的图像。-Content-based image retrieval (Content-based Image Retrieval, referred to as CBIR) techniques have been proposed. T
CBIR
- 基于内容的图像检索 基于颜色、纹理、形状的图像检索 基于区域的图像检索 基于语义的图像检索 相关反馈 -Based on the content-based image retrieval based on color, texture, shape-based image retrieval region-based image retrieval based on semantic image retrieval relevance feedback
CBIR
- 综合多个特征的图像检索，包括颜色、形状和纹理等-Integrated multiple features for image retrieval, including color, shape and texture
ImageRetrieval-master
- CBIR using texture and shape feature
FINAL_CBIR_1187556
- CBIR project using shape moment color
0alaya-cheikh2004
- Query by content, or content-based retri has recently been proposed as an alternative to text-based retri for media such as images, video and audio. Text-based retri is no longer appropriate for indexing such media, for several reasons. Firstly
CBIR
- 基于内容的图像检索，能搜索相似图像。基于颜色，形状和纹理的图像检索。(Content based image retrieval can search similar images. Image retrieval based on color, shape and texture.)