Abstract In last decade, large database of images have grown rapidly and will continue in future. Retrieval and querying of these image in efficient way is needed in order to access the visual content from large database. Content based image retrieval (CBIR) provides the solution for efficient retrieval of image from these huge image database. In this article a hybrid feature based efficient CBIR system is proposed using various distance measure. Spatial domain features including color auto-correlogram, color moments, HSV histogram features, and frequency domain features like moments using SWT, features using Gabor wavelet transform are used. Further, to enhance precision binarized statistical image features, color and edge directivity descriptor features are employed for developing efficient CBIR system. Various distance metrics are used for retrieval. The experiments are performed using WANG database which consists of 1000 images from 10 different classes. Experimental result shows that the proposed approach performs better in terms of precision compared to other existing systems.

中文翻译：

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使用混合特征和各种距离度量的基于内容的图像检索

摘要 在过去的十年中，大型图像数据库发展迅速，并将在未来继续发展。为了从大型数据库中访问视觉内容，需要以有效的方式检索和查​​询这些图像。基于内容的图像检索（CBIR）为从这些庞大的图像数据库中高效检索图像提供了解决方案。在本文中，提出了一种使用各种距离度量的基于混合特征的高效 CBIR 系统。空间域特征包括颜色自相关图、颜色矩、HSV 直方图特征和频域特征，如使用 SWT 的矩、使用 Gabor 小波变换的特征。此外，为了提高精度二值化统计图像特征，颜色和边缘方向性描述符特征被用于开发高效的 CBIR 系统。各种距离度量用于检索。实验使用 WANG 数据库进行，该数据库由来自 10 个不同类别的 1000 张图像组成。实验结果表明，与其他现有系统相比，所提出的方法在精度方面表现更好。