Vector quantization and signal compression
Vector quantization and signal compression
Reduced Complexity Content-Based Image Retrieval Using Vector Quantization
DCC '06 Proceedings of the Data Compression Conference
Compressed domain image retrieval using JPEG2000 and gaussian mixture models
VISUAL'05 Proceedings of the 8th international conference on Visual Information and Information Systems
Storage and retrieval of compressed images
IEEE Transactions on Consumer Electronics
Texture-based medical image retrieval in compressed domain using compressive sensing
International Journal of Bioinformatics Research and Applications
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To reduce the storage and transmission requirements in image applications, images are compressed while maintaining acceptable visual quality. In this paper, image retrieval using Vector Quantization (VQ) is explored. The VQ technique is tested on uncompressed images (UCID) as well as compressed images (JPG). In order to reduce the retrieval time, the images are converted into thumbnails and the retrieval performance in both the domains is observed. . The testing is performed with various thumbnail sizes. Performance is evaluated by using Precision and Recall. It is observed that the retrieval performance using VQ for compressed images remains comparable with that with uncompressed images.