With the huge volume of music clips available for protection, browsing, and indexing, there is an increased
attention to retrieve the information contents of the music archives. Music-similarity computation is an essential
building block for browsing, retrieval, and indexing of digital music archives. In practice, as the number of songs
available for searching and indexing is increased, so the storage cost in retrieval systems is becoming a serious
problem. This paper deals with the storage problem by extending the supervector concept with the binary
hashing. We utilize the similarity-preserving binary embedding in generating a hash code from the supervector
of each music clip. Especially we compare the performance of the various binary hashing methods for music
retrieval tasks on the widely-used genre dataset and the in-house singer dataset. Through the evaluation, we
find an effective way of generating hash codes for music similarity estimation which improves the retrieval
This paper proposes a novel method for content-based watermarking based on feature points of an image. At
each feature point, watermark is embedded after affine normalization according to the local characteristic scale
and orientation. The characteristic scale is the scale at which the normalized scale-space representation of an
image attains a maximum value, and the characteristic orientation is the angle of the principal axis of an image.
By binding watermarking with the local characteristics of an image, resilience against affine transformations can
be obtained. Experimental results show that the proposed method is robust against various image processing
steps including affine transformations, cropping, filtering and JPEG compression.
This paper proposes a methodology in designing a spatial watermark which is robust to geometrical attacks. The proposed watermarking methodology is based on self-registering watermark that tiles the watermark pattern over the entire image. Thus, the peaks in the autocorrelation domain reveals the information about the geometrical transformations which the image has undergone. However, due to the limited precision of the autocorrelation domain, the template search is not reliable enough. The proposed scheme is based on a novel methodology in designing a watermark that is robust to small geometrical attacks. The watermark pattern is designed such that when the synchronization is off by the small amount of geometrical transformations, it can be identified without any searching. This characteristic of the watermark eventually leads to the reduction in search space of the template and compensation for the limited precision of the autocorrelation domain when the synchronization is off by the large amount. The proposed watermark is generated as a filtered white pattern, and in order for the watermark to be robust against geometrical transformation and lossy compression the filter must be carefully designed. The watermark generated by the filter designed by the proposed method has shown improvement in detection reliability.