In this paper, we propose an effective image retrieval approach using block truncation coding compressed data stream based on edge-based quantization (EQBTC). First, an image is compressed into corresponding quantisers and a bitmap image by EQBTC. Then, the quantisers are used for colour feature extraction, whereby the bitmap image and grey image are used for luminance and edge feature extraction. Subsequently, two image features, the colour histogram feature (CHF) and the overall structure feature (OSF), are computed to measure the similarity between two images using a specific distance metric computation. The results presented in this paper demonstrate that the proposed model is superior to the block truncation coding image retrieval scheme and some earlier proposed methods.

中文翻译：

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基于边缘量化的块截断编码的基于内容的图像检索

在本文中，我们提出了一种使用基于边缘量化（EQBTC）的块截断编码压缩数据流的有效图像检索方法。首先，一个图像被 EQBTC 压缩成相应的量化器和一个位图图像。然后，量化器用于颜色特征提取，其中位图图像和灰度图像用于亮度和边缘特征提取。随后，计算两个图像特征，颜色直方图特征（CHF）和整体结构特征（OSF），以使用特定的距离度量计算来测量两个图像之间的相似性。本文中提出的结果表明，所提出的模型优于块截断编码图像检索方案和一些早期提出的方法。