Mukul Majhi completed her B.E in Computer Science and Engineering from the University Institute of Technology, affiliated to University of Burdwan, India in 2013. She obtained her Ph.D. degree in the Department of Computer Science & Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India. She possesses student membership in technical professional organization such as IEEE Membership and also has life membership to the Indian Unit for Pattern Recognition and Artificial Intelligence (IUPRAI). She has contributed a number of research papers in journals and conference proceedings of national and international reputes. Her research area includes content-based image retrieval, security in content-based image retrieval, privacy protection, applied machine learning and image processing.
EDUCATION
B.E - University Institute of Technology, Burdwan, India
Ph.D - Indian Institute of Technology (Indian school of mines), Dhanbad, India
RESEARCH INTERESTS
1. Content based Image Retrieval
2. Privacy Preserving in CBIR
3. Applied Machine Learning
4. Image Security
Secure content-based image retrieval using modified Euclidean distance for encrypted features Mukul Majhi, Arup Kumar Pal, SK Hafizul Islam, Muhammad Khurram Khan Transactions on Emerging Telecommunications Technologies, 2021 In this article, a secure image retrieval scheme is proposed, which focuses on providing satisfactory retrieval results, and the framework searches relevant images even in an encrypted domain without compromising the performance of the retrieval process. Initially, bit‐level features have been endeavored from the luminance component of the image, from which statistical parameters are computed to generate more intrinsic values. These values are subsequently divided into bins to configure two histograms, which effectively reduce the length of the feature vector. These histograms are then eventually combined with quantized chrominance features to enhance the discriminative property of the feature vector. Since the proposed scheme is in the encrypted domain, conventional similarity measure distance for the image is not well suited. So, a modified Euclidean distance is incorporated, which is modeled to work with encrypted features. To comprehend the security, a piecewise logistic map sequence is considered, where seed values are assimilated to generate two secret keys. As a result, not only the system provides an efficient, secure retrieval system but also cryptographic components have no impact on its retrieval efficiency, and satisfactory results are obtained. Experimental results on Corel‐1K and GHIM‐10K illustrate decent performance in retrieval as compared to existing work in the retrieval domain.
An Efficient Content Based Image Retrieval Scheme with Preserving the Security of Images∗ Mukul Majhi, Jitesh Pradhan, Arup Kumar Pal 2019 6th International Conference on Signal Processing and Integrated Networks Spin 2019, 2019 In this paper, an efficient content based image retrieval scheme is proposed which incorporates the security of images in a retrieval system. The main contribution of the proposed scheme is two folded that is to develop an efficient image retrieval process, and to provide security to the retrieved images. To achieve this goal, features from the foreground region as well as background features are extracted, where more importance is given to the foreground region which is identified based on Itti Koch Saliency Map. From the obtained foreground region texture features along with color features are extracted. Simultaneously, the background is divided into four regions and color features are extracted. Finally, the foreground and background features are combined to perform image retrieval process. Now to prevent the feature vector from illegitimate users, suitable cryptographic approaches are used to provide security in terms of confidentiality and integrity. To protect the integrity, the hash value of the feature vector is computed and the obtained hash value along with feature vector are enciphered together. This enciphered value is then communicated to the user. The content owner verifies the integrity of the feature and performs the retrieval process. The retrieved results are then watermarked to protect copyright and are further enciphered so that unauthorized user's cannot access the images. This security mechanism ensures that the retrieved images are shared only to the authorized user. The retrieval process is performed on Corel dataset and the results are comparable to the existing state-of-arts methods. Finally, this process is suitable to protect the security of images in a retrieval system.
Privacy preserving in CBIR using color and texture features Mukul Majhi, Sushila Maheshkar 2016 4th International Conference on Parallel Distributed and Grid Computing Pdgc 2016, 2016 The advent of digital technology and its range of applications in various field witness the importance of retrieving huge and diverse multimedia content from the data repositories. The contents are always under potential threat intended to extract the private information. This paper presents a privacy preserving technique to retrieve images from the corresponding database by using the encrypted feature vector. Texture and quantized HSV color space histogram features are exploited to formulate the feature vector which is encrypted by performing XORed operation with its sliced biplanes by a random binary bit pattern to preserve the hamming distance. Finally, random permutation provide the encrypted feature vector. Experimental results illustrate that the method preserve private information of the content and retrieve relevant images effectively and efficiently.
