Academic Positions

  • Present 2012

    Assistant Professor

    Govt. Engineering College Kozhikode, Dept of Applied Electronics and Instrumentation

  • 2012 2009

    Assistant Professor

    Govt. College of Engineering Kannur, Dept of Electronics and Communication

  • 2008 2008

    Software Engineer

    Network Systems and Technolgies Private Limited, Technopark Trivandrum

  • 2005 2001

    Lecturer in Electronics and Communication Engineering

    MES College of Engineering,Dept. of Electronics and Communication Engineering

Education

  • Ph.D. 2015-

    Ph.D. in Signal Processing(Pursuing)

    National Institute of Technology Calicut

  • M.Tech.2007

    Master of Technology in Signal Processing

    College of Engineering Trivandrum

    University of Kerala

  • B.Tech1998

    Bachelor of Technology in Electronics and Communication Engineering

    Govt. Engineering College Kannur

    University of Calicut, Kerala

Responsibilities and Positions

  • Board of examinations
    M. Tech VLSI Design
    Chairman, Board of examinations of M. Tech VLSI Design, Calicut University.
  • Camp Coordinator
    Assistant Camp Coordinator KTU
    Assistant Camp Coordinator, KTU Valuation Camp at GEC Kozhikode.
  • Board of studies
    Board of studies of ECE
    Member, Board of studies of ECE, Calicut University.
  • Online Data Management
    Managing the online data for KTU, AICTE, NIRF.
    Member, Committee for managing the online data for KTU, AICTE, NIRF.
  • In charge of laboratory
    Faculty in charge of laboratory.
    Faculty in charge of laboratory: Signal processing-PG lab, System simulation lab.
  • Purchase coordinator
    Purchase committee coordinator.
    Department Purchase committee coordinator.
  • Faculty advisor
    Faculty advisor – M. Tech Signal processing
    Faculty advisor – M. Tech Signal processing 2016-18 and 2017-19 batches.

Training and Short Term Courses Details

  • IIT Roorkee 2017
    Complex Analysis and Fourier Analysis

    Course Contents:

    1. Complex Analysis:Complex Plane -Analytic Functions -Complex Integration -Bilinear Transformation -Value distribution theory.

    2. Fourier Analysis: Fourier Coefficients -Sine and Cosine series -Half range series -Convergence -Fourier Integral -Applications.

    3. Special Functions:Beta and Gamma Functions -HypergeometricFunctions -Hermite, Laguerreand Jacobi Orthogonal Polynomials.

    4. Outline of Mathematical Software: Outline related to the above topics in Mathematicasoftware will be provided.


  • IIT Guwahathi 2016
    Algorithms In Engineering

    Algorithm is an important mathematical idea that all students need to understand and use. An algorithm is a finite sequence of rules for solving a particular problem. It has enormous application in modern human life such as mobile, sensor, aerospace, satellite to name a few. Algorithmic study involves applying, developing, analyzing, and understanding the nature of algorithms.

    Engineering students often find difficulties to understand algorithm properly due to poor teaching. The primary objective of the workshop is to bring faculty members from different institutions to share knowledge, skills and techniques of teaching and learning approach. More specifically, the aim of this workshop is to discuss (i) importance of algorithm, (ii) teaching technique to the students, (iii) motivate to do research in algorithms, (iv) some state-of-the-art algorithmic research area, etc.


  • IUAC New Delhi 2014
    Computer interfaced scientific experiments

    Schools and colleges often focus on theory, forgetting that practical experiments teach students much more. Members of Inter University Accelerator Centre (IUAC), an autonomous research institute that provides research facilities to universities, realised the need for experiments in education when teachers and students from other universities visited their university and tried to use a particle accelerator. They were not familiar with computer-controlled experiments that use machines to collect data.

    Dr Ajith Kumar, a scientist at IUAC, wished to provide teachers and students with exposure to this technology and started designing a low-cost device that measured and collected data, and displayed the results graphically on the computer screen.Along with members of the electronics department, he developed Phoenix expEYES—a combination of hardware and software framework for computer-interfaced science experiments that doesn’t require the user to get into the details of electronics or computer programming.


  • IIT Bombay 2013
    GPU Programming and Applications (GPA-2014)

    NVIDIA Corporation, USA has awarded IIT Bombay a CUDA Center of Excellence (CCOE). The CCOE of IIT Bombay, in association with NVIDIA, is conducting a National Level Workshop on GPU Programming and Applications (GPA-2014) during 24th – 26th February 2014 at IIT Bombay. GPA-2014 is a three day workshop on heterogeneous parallel computing. GPA-2014 is aimed at enriching the skills of students, faculty and researchers with cutting-edge techniques and hands-on experience in developing applications for many-core processors, with massively parallel computing resources like GPU accelerators.


  • IIT Madras 2013
    Pedagogy Training

    There are revolutionary changes taking place in the paradigm of teaching-learning process brought out by the availability of new methodologies/technologies for knowledge sharing, and the new context and pressures of increase in and variety of the student population, not to talk of the gradual globalization of the education process itself. Under these circumstances it is essential for the teaching fraternity to hone their existing skills, develop new skills, and learn the nuances of the art, philosophy and science of teaching so that the teaching-learning process becomes more enjoyable, creative and productive, for both the teachers and students. There is need to connect three vital elements of education viz. faculty, student and the process for evolving right mix of solutions among the variety of approaches which significantly vary in different ambience.

    A significant change required in this regard cannot happen by chance and hence a focused effort is needed from committed faculty and the administration.The core team conducts FDPs for faculty from other engineering colleges placed in and around Chennai.

Expert talks delivered

  • GEC Wayanad
    Microprocessors and microcontrollers

    A Talk on Microprocessors and microcontrollers for sixth semester EEE students of Govt. Engineering College Wayanad on 8 th February 2016.


  • GCE Kannur
    Microcontroller programming using embedded C

    A talk on Microcontroller programming using embedded C in the MNAF-2013 organized by Government College of Engineering Kannur on 8th October 2013.


  • GEC Wayanad
    Digital filter design using MATLAB

    A talk on Digital filter design using MATLAB in the Short term training programme on Signal Processing for Communication held at GEC Wayanad from 9-13 July 2012.


  • Womens Poly Kottakkal
    Microcontrollers and interfacing

    A talk on Microcontrollers and interfacing in the visiting faculty programme at Womens poly technic Kottakkal in the year 2012.


Research Projects

  • image

    Sea Navigation and Tracking

    CERD Project 2014

    its a low cost system intended to give warning about the nearby ships to the fishermen.

  • image

    Pattern Recoginition for Smart Classrooms

    TEQUIP 2014

    Its a software tool to convert handwritten characters for online sorting searching and recoginition..

Filter by type:

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Robust single image super resolution using neighbor embedding and fusion in wavelet domain.

Abdu Rahiman V, Sudhish N George at National Institute of Technology Calicut
Journal Paper Computers and Electrical Engineering, Elsevier 2017.

Abstract

This paper proposes methods for super resolving single noisy low resolution images. Even if single image super resolution has been a topic of research for last few decades, super resolution of noisy low resolution images is still a challenging problem. Most of the state of the art super resolution algorithms will fail to perform if significant amount of noise is present in the observed image. In this paper, we propose a denoised patch dictionary based single image super resolution algorithm. To enhance the robustness to noise performance, this method is further modified by using a wavelet based fusion algorithm which combines the result of proposed method with direct super resolved image, and super resolved image after denoising to preserve the finer details of the super resolved image. The proposed methods are applied on the commonly used test images. The results validate that the proposed methods show improvement over the existing techniques.

Single image super resolution using neighbor embedding and statistical prediction model.

Abdu Rahiman V, Sudhish N George at National Institute of Technology Calicut
Journal Paper In Computers and Electrical Engineering August 2017 62:281-292

Abstract

This paper proposes learning based approaches for single image super-resolution using sparse representation and neighbor embedding. Two learning based methods are proposed to recover the high-resolution (HR) image patches from the low resolution (LR) patches. The first method, named as LeNm-SRI, is a computationally efficient approach using neighbor embedding in a partitioned feature space. In this method, the training set is updated by including details extracted from different scales of LR input image. LeNm-SRI, which uses sparse representation invariance, gives acceptable results at low computational load. In the second approach, named as LeNm-RBM, a statistical prediction model is used to predict HR feature coefficients to obtain increased performance. Separate prediction models are trained for each cluster, and the model parameters are updated with each input image, to adapt to input test image. Experimental results validate the computational efficiency and performance of the proposed methods.

A robust face hallucination technique based on adaptive learning method.

Rohit U, Abdu Rahiman V, Sudhish N George at National Institute of Technology Calicut
Conference Papers Multimedia Tools and Applications; Aug 2017, 76 15, p16809-p16829, 21p.

Abstract

Position-patch based approaches have been proposed for single-image face hallucination. This paper models the face hallucination problem as a coefficient recovery problem with respect to an adaptive training set for improved noise robustness. The image-adaptive training set is constructed by corrupting a local training set of position-patches by adding specific amounts of noise depending on the input image noise level. In this proposed method, image denoising and super-resolution are simultaneously carried out to obtain superior results. Though the principle is general and can be extended to most super-resolution algorithms, we discuss this in context of existing locality-constrained representation (LcR) approach in order to compare their performances. It can be demonstrated that the proposed approach can quantitatively and qualitatively yield better results in high noisy environments.

Modified dictionary learning method for sparsity based single image super-resolution.

Rohit U, Abdu Rahiman V, Sudhish N George at National Institute of Technology Calicut
Conference Papers 2016 3rd International Conference on Recent Advances in Information Technology (RAIT).

Abstract

This paper proposes a self-learning based dictionary training approach for single image super-resolution where the low-resolution (LR) and high-resolution (HR) dictionaries are jointly trained using training data set and different scaled versions of the input image. Local variance based salient feature identification is carried out to speed up the super-resolution algorithm. It can be demonstrated that our modified SR algorithm can qualitatively and quantitatively outperform bicubic interpolation and state-of-the-art methods..

SVM based feature set analysis in dynamic malayalam handwritten character recognition.

Steffy Maria Joseph ,V Abdu Rahiman , K. M. Abdul Hameed
Conference Papers 2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).

Abstract

This paper proposes a self-learning based dictionary training approach for single image super-resolution where the low-resolution (LR) and high-resolution (HR) dictionaries are jointly trained using training data set and different scaled versions of the input image. Local variance based salient feature identification is carried out to speed up the super-resolution algorithm. It can be demonstrated that our modified SR algorithm can qualitatively and quantitatively outperform bicubic interpolation and state-of-the-art methods.

Face Hallucination using Eigen Transformation in Transform Domain.

Abdu Rahiman V, Jiji Victor Charangatt
Journal Paper International Journal of Image Processing (IJIP) Volume(3), Issue(6), Pages - 265 – 282, January 2010

Abstract

Faces often appear very small in surveillance imagery because of the wide fields of view that are typically used and the relatively large distance between the cameras and the scene. In applications like face recognition, face detection etc. resolution enhancement techniques are therefore generally essential. Super resolution is the process of determining and adding missing high frequency information in the image to improve the resolution. It is highly useful in the areas of recognition, identification, compression, etc. Face hallucination is a subset of super resolution. This work is intended to enhance the visual quality and resolution of a facial image. It focuses on the eigen transform based face super resolution techniques in transform domain. Advantage of eigen transformation based technique is that, it does not require iterative optimization techniques and hence comparatively faster. Eigen transform is performed in wavelet transform and discrete cosine transform domains and the results are presented. The results establish the fact that the eigen transform is efficient in transform domain also and thus it can be directly applied with slight modifications on the compressed images.

Traffic Sign Detection and Pattern Recognition Using Support Vector Machine.

Kiran C.G, Lekhesh V. Prabhu , Abdu Rahiman V. , Rajeev K.
Journal Paper ", ICAPR, 2009, Advances in Pattern Recognition, International Conference on, Advances in Pattern Recognition, International Conference on 2009, pp. 87-90

Abstract

Abstract: A vision based vehicle guidance system must be able to detect and recognize traffic signs. Traffic sign recognition systems collect information about road signs and helps the driver to make timely decisions, making driving safer and easier. This paper deals with the detection and recognition of traffic signs from image sequences using the colour information. Colour based segmentation techniques are employed for traffic sign detection. In order to improve the performance of segmentation, we used the product of enhanced hue and saturation components. To obtain better shape classification performance, we used linear support vector machine with the Distance to Border features of the segmented blobs. Recognition of traffic signs are implemented using multi-classifier non-linear support vector machine with edge related pixels of interest as the feature.

Face Hallucination Using PCA in Wavelet Domain.

Abdu Rahiman V, Jiji Victor Charangatt
Conference Papers In Proceedings of the Third International Conference on Computer Vision Theory and Applications(VISAPP 2008), Funchal, Madeira, Portugal, Volume 1, January 22-25, 2008

Abstract

Faces often appear very small in surveillance imagery because of the wide fields of view that are typically used and the relatively large distance between the cameras and the scene. In applications like face recognition, face detection etc. resolution enhancement techniques are therefore generally essential. Super resolution is the process of determining and adding missing high frequency information in the image to improve the resolution. It is highly useful in the areas of recognition, identification, compression, etc. Face hallucination is a subset of super resolution. This work is intended to enhance the visual quality and resolution of a facial image. It focuses on the Eigen transform based face super resolution techniques in transform domain. Advantage of Eigen transformation based technique is that, it does not require iterative optimization techniques and hence comparatively faster. Eigen transform is performed in wavelet transform and discrete cosine transform domains and the results are presented. The results establish the fact that the Eigen transform is efficient in transform domain also and thus it can be directly applied with slight modifications on the compressed images.

Currrent Teaching

  • Present PHD

    Optimization Techniques

    09AE7187 Optimization Techniques – for odd semester PhD course work.

  • Present MTech

    Speech and Audio Processing

    09AE7117 Speech and Audio Processing – S3 - M Tech signal processing 2016-18 batch.

  • Present BTech

    Communication systems Lab

    EC14 707(P) Communication systems Lab – S7 BTech ECE - 2014-18 batch.

Teaching History

  • Past BTech

    Computer Organisation and Architecture

    EC14 501:Computer Organisation and Architecture.

  • Past BTech

    Microwave Engineering

    EC14 702:Microwave Engineering.

  • Past BTech

    Advanced Instrumentation

    AI09 702:Advanced Instrumentation.

  • Past BTech

    Power Electronics

    AI09 505:Power Electronics.

  • Past BTech

    Digital Signal Processing

    AI09 601:Digital Signal Processing.

  • Past BTech

    System Simulation Lab

    AI09 707(P):System Simulation Lab.

  • Past MTech

    Adaptive Signal Processing

    09AE6132:Adaptive Signal Processing.

  • Past MTech

    Random Process for Applications

    09AE6131:Random Process for Applications.

  • Past MTech

    DSP Systems Lab

    09AE6171:DSP Systems Lab.

  • Past MTech

    Signal Processing Lab

    09AE6172:Signal Processing Lab

MTech Students and Thesis

  • MTech
    M. Tech Thesis

    2016-18 batch

    1.Princy N R: Multi-frame image restoration using ADMM in a tensor frame work.

    2015-17 batch

    1. Jesna Augastine: Learning based text image super resolution.

    2. Thahira M: Neighbour embedding based face image super resolution.

    3. Jesleena : Multiframe super resolution using iterative algorithms - Co-guide.

    2014-16

    1.Junaid : SVD based single image super resolution.

    2.Thanooja L: Fast matting algorithm for robust text image super resolution.

    2012-14

    1.Rafeeque TP: Super Resolution of MRI images in spatial and wavelet domain.

    2.Jabir K: Comparison of Threshold Selection Methods for Wavelet Based MRI Image De-noising

    3.Steffy Maria Joseph: Online Malayalam handwritten character recognition- Co-guide.

BTech Students and Project

  • BTech
    B.Tech Projects

    S7 ECE – 2014-18 batch

    1. Smart Aid for Blind.

    1.1.1. Aneesa c.k -05

    1.1.2. Anjusree b.p- 08

    1.1.3. Aswani v.t -14

    1.1.4. Jumana jabin m.k -27

    1.1.5. Thamjeeda k.m -47


    2. Sign language glove with speech synthesizer.

    2.1.1. AISWARYA K.H -03

    2.1.2. SACHIN K MOHAN-38

    2.1.3. SIVADETH S-44

    2.1.4. VISHNU PRASAD P S-51

    2.1.5. DEVAPRASAD K K-56

At My Office

You can find me at my office located at first floor of Dept. of Applied Electronics and Instrumentation GEC Kozhikode.

I am at my office every day from 9:30AM until 4:30PM, but you may consider a call to fix an appointment.