VCC-BPS: Vertical Collaborative Clustering using Bit Plane Slicing

The vertical collaborative clustering aims to unravel the hidden structure of data (similarity) among different sites, which will help data owners to make a smart decision without sharing actual data. For example, various hospitals located in different regions want to investigate the structure of common disease among people of different populations to identify latent causes without sharing actual data with other hospitals. Similarly, a chain of regional educational institutions wants to evaluate their students’ performance belonging to different regions based on common latent constructs. The available methods used for finding hidden structures are complicated and biased to perform collaboration in measuring similarity among multiple sites. This study proposes vertical collaborative clustering using a bit plane slicing approach (VCC-BPS), which is simple and unique with improved accuracy, manages collaboration among various data sites. The VCC-BPS transforms data from input space to code space, capturing maximum similarity locally and collaboratively at a particular bit plane. The findings of this study highlight the significance of those particular bits which fit the model in correctly classifying class labels locally and collaboratively. Thenceforth, the data owner appraises local and collaborative results to reach a better decision. The VCC-BPS is validated by Geyser, Skin and Iris datasets and its results are compared with the composite dataset. It is found that the VCC-BPS outperforms existing solutions with improved accuracy in term of purity and Davies-Boulding index to manage collaboration among different data sites. It also performs data compression by representing a large number of observations with a small number of data symbols.

Bit Plane Slicing, Wavelet and Polynomials Mixing for Image Compression

This paper introduced a hybrid technique for lossless image compression of natural and medical images; it is based on integrating the bit plane slicing and Wavelet transform along with a mixed polynomial of linear and non linear base. The experiments showed high compression performance with fully grunted reconstruction.

Bit Plane Slicing Based Digital Watermarking Technique in Dwt Domain

Authenticity of image and its copyright protection are one of the essential application of watermarking. In this paper, a hybrid technique for watermarking in DWT domain is presented for its application in the field of providing authentication to images. In this work binary image is used as watermark and is embedded in the 'host image'. Before embedding the watermark in the host, the host image is splitted into 8 bit planes using bit plane slicing. Followed that DWT is applied to the least significant bit plane which partitions the respective plane into low frequency (LL subband) and high frequency (HH, HL and LH subbands). The SVD is applied to HH subband of least significant bit plane and watermark is embedded on the singular matrix part of SVD. To analyse the robustness of the scheme proposed in this paper, watermarked image is attacked by different image processing attacks. Original watermark and extracted watermark is compared on the scale of normalized correlation to measure the robustness of the scheme against various attacks.