Aisha Ajmal

Work place: Department of Electrical Engineering, Sultan Qaboos University, Muscat, Oman



Research Interests: Medical Image Computing, Image Processing, Image Manipulation, Image Compression, Computer Vision


Aisha Ajmal, female, is a Lecturer in the Department of Computer Engineering, (SSUET). She did her BS from SSUET and doing her MS from the same university. Currently she is pursuing her MS thesis in image processing. Her research areas in image processing includes vehicle detection, object detection in complex scenes, biomedical image processing and computer vision.

Author Articles
Improved Bit Plane Splicing LSB Technique for Secret Data Hiding in Images Using Linear Congruent Method

By Ibrahim M. Hussain M. Kamran Khan Mohammad Naseem Aisha Ajmal Osama M. Hussain

DOI:, Pub. Date: 28 Jul. 2012

In this paper, we propose two algorithms based on the popular Bit Plane Splicing Least Significant Bit (LSB) Technique for secret data hiding inside images. One major disadvantage of Bit Plane Splicing LSB technique is its low hiding capacity which results in severe degradation of the cover image upon hiding large amount of data. The proposed algorithms overcome this issue by imposing hiding rules based on the intensity level of pixels. In addition the method for data hiding is done in a non sequential manner using linear congruent random number generators. Experiment results show that the proposed techniques called Optimum Intensity Based Distributed Hiding (OIBDH) technique and Linear Congruent Optimum Intensity Based Distributed Hiding with Key (LC-OIBDH-k) outperforms Bit Plane Splicing LSB technique as they have better hiding capacity with less degradation in the cover image. Furthermore, the proposed algorithms are tested using absolute entropy curves and results show that our proposed techniques have lower absolute entropy difference compared to Bit Plane Splicing LSB technique in all the tested images and for different secret data sizes.

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