Content-based image retrieval using block truncation coding based on edge quantization
Yanhong Chen, Ching‐Chun Chang, Cheng-Yi Hsu · Connection Science · 2020
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.