Quality-based iris segmentation-level fusion

Iris localisation and segmentation are challenging and critical tasks in iris biometric recognition. Especially in non-cooperative and less ideal environments, their impact on overall system performance has been identified as a major issue. In order to avoid a propagation of system errors along the processing chain, this paper investigates iris fusion at segmentation-level prior to feature extraction and presents a framework for this task. A novel intelligent reference method for iris segmentation-level fusion is presented, which uses a learning-based approach predicting ground truth segmentation performance from quality indicators and model-based fusion to create combined boundaries. The new technique is analysed with regard to its capability to combine segmentation results (pupillary and limbic boundaries) of multiple segmentation algorithms. Results are validated on pairwise combinations of four open source iris segmentation algorithms with regard to the public CASIA and IITD iris databases illustrating the high versatility of the proposed method

IRDO: Iris Recognition by Fusion of DTCWT and OLBP

Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using Fusion of Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP) Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI) area from an iris. The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP using arithmetic addition. The Euclidean Distance (ED) is used to compare test iris with database iris features to identify a person. It is observed that the values of Total Success Rate (TSR) and Equal Error Rate (EER) are better in the case of proposed IRDO compared to the state-of-the art technique

Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan

The doctoral research abstract. Vol:9 2016 / Institute of Graduate Studies, UiTM

FOREWORD: Seventy three doctoral graduands will be receiving their scroll today signifying their achievements in completing their PhD journey. The novelty of their research is shared with you through The Doctoral Abstracts on this auspicious occasion, UiTM 84th Convocation. We are indeed proud that another 73 scholarly contributions to the world of knowledge and innovation have taken place through their doctoral research ranging from Science and Technology, Business and Administration, and Social Science and Humanities. As we rejoice and celebrate your achievement, we would like to acknowledge dearly departed Dr Halimi Zakaria’s scholarly contribution entitled “Impact of Antecedent Factors on Collaborative Technologies Usage among Academic Researchers in Malaysian Research Universities”. He has left behind his discovery to be used by other researchers in their quest of pursuing research in the same area, a discovery that his family can be proud of. Graduands, earning your PhD is not the end of discovering new ideas, invention or innovation but rather the start of discovering something new. Enjoy every moment of its discovery and embrace that life is full of mystery and treasure that is waiting for you to unfold. As you unfold life’s mystery, remember you have a friend to count on, and that friend is UiTM. Congratulations for completing this academic journey. Keep UiTM close to your heart and be our ambassador wherever you go. / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR