实验结果表明，综合特征检索要比单独使用某一特征检索效果更好。
Experimental results show that an integrated search feature is better than the individual characteristic.
在检索中，颜色和纹理特征的权重不同，本文采用线性加权方式综合颜色特征相似距离和纹理特征相似距离，对图像进行检索。
In this paper, we using a kind of comprehensive image retrieval which fuses color and texture features by linear weights and discuss the method which the weights are determined.
综合叶片的离心率、似圆率和这两个边界曲率特征来检索叶片数据库，进行形状匹配，实现叶片自动分类。
The system retrieved and classified the leaf by shape matching with the samples in a leaves database by eccentricity, circularity and the curvature features.
提出一种综合利用文档图像的段落特征和局部像素分布相对差特征进行文档图像检索的方法。
This paper proposes document image retrieval method based on the paragraph feature combining up with the local relative difference of pixel distributions.
主要讨论了在图像检索中使用的各种特征、多特征检索的优点与可行性，以及用多特征综合检索需要解决的几个问题。
The paper has discussed various kinds of features and the advantages and feasibility of multi-features retrieval as well as several problems in multi-feature retrieval.
本文介绍了基于纹理特征的特征提取方法和中心特征的提取方法，并进而提出了一种综合利用上述两个特征共同进行检索的方法。
In this paper, out methods for image retrieval using center and texture features are firstly discussed. Furthermore, a new method for image retrieval using combined center and texture is proposed.
为了充分利用商标图象的内部信息，以提高商标图象的检索精度，提出了一种综合利用商标形状特征与其内部空间位置关系特征来检索二值商标图象的方法。
This paper presents a trade mark retrieval method in which the shape feature and spatial relationship are both used for the purpose of making full use of image info and improving retrieval precision.
在图像主目标区域确定的基础上，提出了基于主目标区域的图像颜色特征的综合检索方法。
With the confirm of the object region in image, a color image retrieval algorithm based on the main object region of the image is presented.
而综合颜色和纹理特征算法的检索结果更优于单一特征算法。
Furthermore, the retrieval results using the proposed combination color and texture features method are more precise than the single feature method.
提出一种综合利用文档图像的段落特征和局部像素分布相对差特征进行文档图像检索的方法。
Ordinary document image retrieval algorithms can be classed into two classes, character content (OCR) based method and image level feature based method.
实验结果表明，综合低级特征和语义特征的检索比仅利用低级特征的检索更接近于人的视觉理解。
Experiment results show that the retrieval result by low features and semantic features are better than only by low features.
由于综合利用了图像的颜色及纹理特征，实验结果表明，该方法取得了较好的检索效果。
Experimental results show that the new method is efficient and it provides noticeable improvement to the performance of image retrieval.
基于单一特征的图像检索往往顾此失彼，无法综合各特征的优势。
Single feature-based image retrieval often catches one and loses another, so it can't integrate the advantages of each feature.
通过对真实图像数据的检索实验表明：综合两种特征检索图像比单一特征检索效果更好。
The results show that the retrieval results obtained from combined-features are superior to that obtained from single-features.
通过对真实图像数据的检索实验表明：综合两种特征检索图像比单一特征检索效果更好。
The results show that the retrieval results obtained from combined-features are superior to that obtained from single-features.
应用推荐