Dr. HARISH KUMAR   E‐mail: [email protected], harish‐[email protected]  Tel: +33524574049, Mob: +33658996257,  Fax: +33524574124     the sustainable development of local An enthusiastic researcher, motivated for   decision support, particularly using environmental information, with and for the   human  kind

CURRICULUM VITAE Name: Date of birth: Civil status: Nationality: Permanent Address: Present Address: Official Address:

Dr. Harish Kumar 26 November 1980 Single Indian # 7, RMS Colony, Sanjaynagar, Bangalore, Karnataka- 560094, India. Ph: +918023410605 RES. teneo Medoquine, APT 07, 16 Avenue de la vielle tour, Talence 33400 Office 24, GeoStat, INRIA Bordeaux Sud Ouest, Bât A29 bis 351, Cours de la Libération, Talence - 33405

RESEARCH INTERESTS Digital Image Processing, Signal Processing, Pattern Recognition, Computer Vision, Algorithm Development, Optical and Radar Remote Sensing, Astronomical Images, Physical Optics, Fuzzy Logic, Heartbeat Dynamics and Microcanonical Multifractal Formalism.

EDUCATION PDF (Post Doctoral Fellow) in Team INRIA (Second top organizations in Computer Science for Europe (http://academic.research.microsoft.com)) Bordeaux -- Sud-Ouest, GeoStat Team, France from November 2010 (I was one of the 53 competitive International applicants) Thesis Title: Non-linear approaches in the analysis of the dynamics of complex signals: the case of cardiac signals (Funded by Ministry of Research subvention Grant) Supervisor: Dr. Hussein Yahia Keywords of work: Heart-beat Dynamics, MMF (Microcanonical Multifractal Formalism) Synopsis of PDF work: - Analysis of complex systems and signals especially the heartbeat signals with non-linear methods involving multiscale approaches. The work involves a new phase of analyzing the complex signals, in which the acquisition signals are considered as realizations of complex

dynamic systems; therefore one seeks quantities and parameters that are known to play a key role in these complex dynamic systems (singularity exponents). The purpose of this work is to develop and implement these new tools for analyzing complex signals in a particular and socially important case: the analysis of cardiac signals associated to atrial fibrillation. Atrial fibrillation (AF), the most common form of cardiac arrhythmia, is responsible for significant morbidity each year in all parts of the world. It results from a chaotic operation located at the top of the heart (atria), which becomes ineffective. Although it is not a priori in itself a severe condition, it causes a high mortality rate by its most dreaded complications. This project aims to provide tools to understand more precisely the complex dynamics associated with cardiac signals acquired by internal catheters, to explore how these tools can be associated to methods of statistical learning and classification in the study of these signals, and to examine their relevance in terms of new tools for diagnosis. PhD (Doctor of Philosophy) in Computer Science and Engineering, Indian Institute of Technology Roorkee, India, March 2011 (Got 'A' grade from both Indian and foreign examiner) Thesis Title: Fusion Approach on Low Resolution Satellite Images for Land Cover Application (Funded by Ministry of HRD, Govt. of India) Supervisor: Dr. Dharmendra Singh Keywords of PhD work: - Fusion Technique, Optical and radar imaging, Fourier/harmonic/time series analysis, supervised and unsupervised classification, Curvelet transform, ATrous wavelet transform, Binary division algorithm, Fuzzy based methods. Synopsis of PhD work: Satellite remote sensors can be divided into two major types of imaging systems: optical (optical and thermal) and radar imaging systems. Optical imaging systems operate in the visible and IR (Infra Red) regions of the spectrum. Their operational use is weather dependent, since clouds are not transparent at visible/IR wavelengths (0.4-14 μm). Some of the satellite images working on optical and thermal images can be listed as AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), Landsat (land Satellite), LISS (Linear Imaging Self Scanner), SPOT (Satellite Pour L’Observation de la Terra or earth observing satellites) and many others. On the other hand, radar imaging systems works in microwave region (1 GHz to 30 GHz), and are very much atmosphere and weather independent. ERS (European remote sensing

satellite), JERS (Japanese earth remote sensing), ENVISAT (Environmental Satellite Advanced Synthetic Aperture Radar), RADARSAT (Radar Satellite), and PALSAR (Phased Array L-band Synthetic Aperture Radar) are some of the radar satellite sensors available for various applications. One of the important applications of satellite image processing is the generation of landuse/ land-cover maps in comparison to more traditional mapping approaches such as terrestrial survey and basic aerial photo interpretation which is quite cumbersome. Land-use mapping/ classification using satellite imagery has the advantages of low cost, large area coverage, repetitively, and computitivity. Eventually maximum high resolution satellite images are expensive with some extent. Therefore, it is need of current research to explore some techniques by which utilization of freely available satellite image may be enhanced. The availability of MODIS image with greatly improved spectral, spatial, geometric, and radiometric attributes provides significantly new opportunities and challenges for remote sensingbased land cover classification as well as other applications. MODIS has several spectral bands with are useful for various application in one hand and in other hand its spatial resolution varies from 250 m to 1000 m. This spatial resolution is not so enough to get good classification accuracy on MODIS images. Therefore, there is a need to explore the possibility of the use of techniques like fusion that may be helpful to increase the utilization of MODIS image for land cover classification/ land use maps. Hence in this work, exploration of the fusion technique for enhancing the land cover classification of low resolution satellite image especially freely available satellite image like MODIS has been made. Subsequently analyzing the effect of classification accuracy on major type of land cover types like agriculture, water and urban bodies with fusion of ASTER image to MODIS image and enhance the classification accuracy of MODIS image at spatial level. For this purpose, we have considered to fuse, high resolution i.e., like 15m resolution ASTER image with moderate resolution i.e., like 250 m MODIS satellite data. MODIS band 1 and band 2 are used as a moderate resolution data, where as ASTER band 2 and band 3 are considered as high resolution data. Curvelet transformation has been applied for fusion of these two satellite images and Minimum Distance classification technique has been applied on the resultant fused image for classifying the fused image in major land cover classes (i.e., agriculture, urban and water). The fuzzy based fusion is also applied for fusion of these two satellite images. After the fusion by fuzzy based approach, the minimum distance classification technique is used to classify the resultant fused image in major land cover classes (i.e., agriculture, urban and water). It is quantitatively observed that the overall classification accuracy of MODIS

image after fusion is enhanced at spatial level. The quality of fused image is assessed by quality indicators. Another important point which one should consider while doing the time-series analysis, where every MODIS image may require the same number of high resolution image for fusion in one hand and in another hand every time one has to carry out the complex computation of fusion. Generally high resolution image i.e., ASTER is not freely available. So, it is another point of research to develop such a methodology or coefficients by which use of high spatial resolution image (i.e., ASTER in our case) for fusion for time series analysis may be minimized. Hence, we have attempted to explore to find the possible methodology to search some fusion coefficient by which ASTER image use may be minimized, while analyzing time series image for observing the land cover classification. Another advantage of this fusion coefficient is that every time we do not have to carry out curvelet transform on ASTER image by which it reduces the computation complexity up to a certain extent. The researchers have demonstrated the benefit of combining optical and radar image for improved land cover mapping in several studies. With the availability of multifrequency and high-resolution space borne radar data, such as Advanced Land Observation Satellite (ALOS) Phase Array L-type Synthetic Aperture Radar (PALSAR), an increased interest in tools to exploit the full information content of both image types is arising. Therefore, we have considered the fusion of different sensors image like optical and radar images (where both can provide the complimentary information) and subsequently the quality of fused image is assessed by various assessment indicators. Hence an attempt has been made to fuse the PALSAR image with MODIS image using curvelet based fusion and quality assessment of fused image has been done. PALSAR image has a advantage of availability of image in four different channels. These four channels are HH (Transmitted horizontal polarization and received also in horizontal polarization), HV(Transmitted horizontal polarization and received vertical polarization), VH (Transmitted vertical polarization and received horizontal polarization) and VV (Transmitted vertical polarization and received vertical polarization), which provides various landcover information. We have used the curvelet and fuzzy based technique for fusing the PALSAR (HH, HV and VV) image to MODIS (band 1 and 2) image in spatial resolution. Each band of PALSAR (i.e., HH, HV and VV) is individually fused with MODIS band 1 and Band 2 separately in one hand and in other hand fused image of MODIS band 1 and 2 is individually fused PALSAR (HH, HV and VV) bands separately. The quality of fused image is assessed by assessment indicator like Correlation, RMSE (root mean squared error), Relative Mean Difference, Relative Variation

Difference, Deviation Index, PSNR (Peak signal-to-noise ratio) and Universal Image Quality Index. These indicators are applied to measure and compare the performance of the fused images. The results are quite encouraging and good overall classification accuracy after fusion was obtained. Thereby in near future it may provide a better platform for maximize the use of MODIS images. Unsupervised clustering is a fundamental tool in image processing for geosciences and satellite imaging applications. Unsupervised clustering is often used to obtain vegetation maps of an area of interest in the satellite image processing domain. This approach is useful when reliable training image are either scarce or expensive, and when relatively little a priori information about the image is available. Eventually this unsupervised clustering can be used for hotspot and non-hotspot region classification. For this purpose, we have considered Jharia, region of India as a test area. We have explored the application of MODIS and LISS-III image for hotspot and non-hotspot regions. Although MODIS provides a special product MOD14A2 for fire product classification (Surface fires). But this special product is not only sufficient for hotspot and non-hotspot regions (Sub-surface fires). Therefore, in this work, an approach based on Binary Division Algorithm is used for hotspot and non-hotspot regions using band 1 and band 2 of MODIS and band 2 and band 3 of LISS – III, for the Jharia (India) Region. Results are compared with the MOD14A2, the exclusive MODIS product for thermal anomalies and fire, and it is found that the proposed approach gives quite satisfactory results in comparison to MOD14A2 products. Recent advances in satellite image processing have expanded opportunities to characterize the seasonal and inter-annual dynamics of natural and managed Land use/ land cover communities. The development of a regional-scale monitoring procedure is challenging because it requires remotely sensed image that have wide geographic coverage, high temporal resolution, adequate spatial resolution and minimal cost. The MODIS offers an opportunity for detailed, large-area Land use/ land cover characterization by providing global coverage of science quality image with high temporal resolution (1–2 days) and intermediate spatial resolution. The spatial, spectral, and temporal components of the MODIS may be appropriate for multitemporal harmonic analysis. Harmonic analysis is useful for analyzing seasonal and inter-annual variation in land surface condition. This type of analysis may develop the possibility to quantify and classify some fundamental characteristics, related to the phenology of vegetation, water and others. Hence, we have tried to characterized the changes for agricultural and water land use/land cover in Western Utter Pradesh and part of Uttarakhand

of India form the year 2001 to 2008. In this perspective, we have considered the MODIS NDVI (Normalized difference vegetation index) and NDWI (Normalized difference water index) images for agricultural and water regions respectively. Harmonic analysis, also known as Fourier analysis, decomposes a time-dependent periodic phenomenon into a series of sinusoidal functions in which each defined by unique additive and amplitude values. In consequence, the additive image A0 and the amplitude images A1 were produced, respectively. With these images we have checked the changes in agricultural and water land use/land cover in the test area, in one hand we have analyzed the changes or variation in agriculture and water for the whole image, whereas in the other hand, we have analyzed the changes or variation in agriculture and water for the selected region of interest. Such type of study is very helpful in near future to optimize the use of MODIS image in one hand and in another hand to develop monitoring system by which changes during the particular month may be observed. The main aim of this work was to study and to maximize the utilization of low resolution freely available satellite image for various land cover applications. M.Tech (Master of Technology) in Computer Cognition Technology, Mysore University, India, December 2004 Marks (%): 87.8 (Out of 100) Project Details: “Damage classification on Infra-Red Images of composite specimens through Image Analysis methods” was successfully conducted at National Aerospace Laboratories, Bangalore. Abstract: In the aircraft body, there are certain defects like Delamination or Disbond and Fluid Intrusion. A system was developed, that would automatically classify the damages or the defects that are present in the aircraft body through the image analysis method. A System that comprises, a supervised classification, is applied on the infra-red image of the aircraft body, to detects the defects and also to classify these defects. B.E. (Bachelor of Engineering) in Computer Science & Engineering, Visveswaraiah Technological University, India, July 2002 Marks (%): 64.32 (Out of 100) Project Details: “System Monitoring Tools”, successfully conducted at Center for Military Airworthiness & Certification(CEMILAC), Ministry of Defense (R&D), Bangalore. Abstract: A Graphical User Interface based software package "System Monitoring Tools", developed in Visual C++ 6.0. This package consists of monitoring tools, i.e., Processor monitoring tool, Disk monitoring tool and

RAM monitoring tool. The processor monitoring tool, monitors the CPU speed, the cache hit, the processor time. The disk monitoring tool would monitor the Disk time, Disk Transfers/sec and disk usage. The Ram monitoring tool would monitor only the memory usage

TECHNICAL SKILLS Digital Image Processing, Digital Signal Processing, Optical and Radar Remote Sensing, Fourier/Harmonic/ Time series analysis, Pattern Recognition, Data Structure & Algorithm, Advance Data Structure, Design & Analysis of Algorithms, Software Engineering, Concepts of Operating System, Computer Architecture, Theory of Computation, Computer Networks, Optimization Techniques, Computer Vision, fuzzy based methods and Biomedical Signal Processing (Heart-beat Signal).

SOFTWARE SKILLS Programming Languages: Proficient in C, C++, JAVA, IDL (ENVI), MATLAB. Operating Systems: Hands-on experience with Dos, Windows 95/98/2000/XP/Vista/W7, and Linux (Redhat, Suse and Ubuntu) Software Experience: Expertise in ArcInfo, Arcview, ArcMap, ENVI, ERDAS Imagine and IdRISI, Sarscape.

IMAGING SYSTEMS USED: NOAA/AVHRR, MODIS, ASTER, LANDSAT, CARTOSAT-1, PALSAR.

LANGUAGES KNOWN English, Kannada and Hindi

AWARDS/ ACHIEVEMENTS Young Scientist Award 2010, by Second National Young Scientist Symposium 2010 at Doon university, Dehradun, Uttarakhand, India. Title of Research Paper: - Fusion of MODIS and PALSAR Data using ATrous Transform for land cover enhancement. Abstract: - It is a current need of research to extensively use the freely available satellite images Moderate Resolution Imaging Spectroradiometer (MODIS). The problem with these images are its poor spatial resolution that restricts its use in various applications. This restriction may be minimized by application of the fusion techniques where high resolution image will be used to fuse with low resolution images. Another important aspect of fusion of different sensors data like optical and radar images (where both can provide

the complimentary information) and the resultant fused image after fusion may give enhanced and some useful information that may be beneficial for various application. Therefore in this paper an attempt has been made to fuse the full polarimetric Phased Arraytype L-band SAR(PALSAR) image with MODIS image and assess the quality of fused image. PALSAR image has a advantage of availability of data in four different channels. These four channels are HH(Transmitted horizontal polarization and received also in horizontal polarization), HV(Transmitted horizontal polarization and received vertical polarization), VH (Transmitted vertical polarization and received horizontal polarization) and VV (Transmitted vertical polarization and received vertical polarization), which provides various landcover information. The Atrous Wavelet fusion technique has been applied for MODIS band 1 and 2 and PALSAR HH(, HV and VV bands for assessing the effect of fusion in land cover distinction. The three major land covers agriculture, urban and water are considered for evaluation of fusion of these images for the Roorkee area of India. The results are quite encouraging and in near future it may provide a better platform for the maximize the use of MODIS images. Samsung Global Internship Program 2008 in Samsung Electronics Co Ltd, Suwon, South Korea (I was one among the 15 students selected globally, and one among 2 students from India, selected for the year 2008). Division: Mechatronics & Manufacturing Technology Center, Corporate Technology Operations. Title: TFT-LCD Defect Classification (4 Weeks) I was one among the 15 students selected globally, and one among 2 students from India, selected for the year 2008. Abstract: - In recent years, the TFT-LCD gradually becomes a mainstream of FPDs (Flat Panel Displays), and the request of image quality for a TFT-LCD becomes more and more severe. There are many items such as luminance, chromaticity, contrast, flicker, crosstalk and response time, etc. have to be evaluated for the image quality of display devices. But several of the other items have difficulties during evaluation of image quality, e.g. Mura. Mura is the most popular defect in producing TFT-LCD, in most cases, and is not easily identified so that those persons identifying mura in the industry need the experienced skill based on the related knowledge. It is thus obvious for manually identifying process by human beings to be costly and inconsistent. To overcome such hardship, an automated process for Mura analysis has been considered. In this study, we have investigated a LCD image with Mura defect and a False alarm(which pretends to be a defect but actually no defect) and the last

is an LCD image with no defect. So in this study, we have designed an algorithm that classify the given LCD image into three regions efficiently and accurately.

RESEARCH PUBLICATIONS ¾ Harish Kumar G R and Dharmendra Singh, “Application of Binary Division Algorithm for Image Analysis and Change Detection to identify the hotspots in MODIS Images” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 36, Part 4, pp. 140-145, 2006. ¾ Harish Kumar G R, B M Patil, Ramanna S Havinal, “Pattern classification of binary data using adaptive resonance theory-1”, Proceedings of the IEEE 1st International Conference on Signal and Image Processing, pp. 270-273, 2006. ¾ Harish Kumar G R, Dharmendra Singh, Ankush Mittal,” Fusion of MODIS, AVHRR and ASTER data using curvelet transform for land cover classification”, Geoscience and Remote Sensing Symposium, IGARSS 2007, IEEE International, Page(s): 3082-3085, 2007. ¾ Harish Kumar G R and Dharmendra Singh, “A Pixel Purity Index and Curvelet based approach for the Fusion of ASTER and MODIS data for land cover classification”, 37th COSPAR Scientific Assembly, Canada (http://adsabs.harvard.edu/abs/2008cosp...37.2920S), 2008. ¾ Harish Kumar G R and Dharmendra Singh, “Application of Cluster Based Approach to Enhance the Land Cover Classification Accuracy in MODIS Images”, Symposium 2009, 17-19 September, pp. 55, 2009. ¾ Harish Kumar G R and Dharmendra Singh, "Fusion of MODIS and ASTER data using fuzzy logic", National Seminar on Radar Remote Sensing and Its Applications, IIT Roorkee, 25-26 September, pp. 25, 2009. ¾ Harish Kumar G R and Dharmendra Singh, " Fusion of MODIS and PALSAR Data using ATrous Transform for land cover enhancement" Ucost, 6-7 February 2010. ¾ Harish Kumar G R and Singh D, "Quality assessment of fused image of MODIS and PALSAR". Progress In Electromagnetics Research B, Vol. 24, 191221, 2010 (Impact factor :4.735) ¾ Harish Kumar G R and Dharmendra Singh, “Fusion of MODIS and PALSAR principal component images through curvelet transform for land cover classification", 38th COSPAR Scientific Assembly, Germany (http://adsabs.harvard.edu/abs/2010cosp...38..388S), 2010. ¾ Harish Kumar G R and Dharmendra Singh, "Curvelet Based Fusion of MODIS and ASTER data", under 4th review in Advances in Space Research, ELSEVIER (communicated in Jan 2009).

¾ Harish Kumar G R and Dharmendra Singh, "  Multitemporal Harmonic Analysis of MODIS indexes images from the year 2001 to 2008", communicated to Geomatics, Natural Hazards and Risk, Taylor & Francis (communicated in Mar 2010). ¾ Harish Kumar, Hussein Yahia and Singh D., “A detailed analysis of multisensor fusion of moderate resolution imaging spectroradiometer”, 19th European Signal Processing Conference (EUSIPCO 2011), EURASIP, ISSN 2076-1465, pp. 1145-1149, 2011. ¾ Harish Kumar, Hussein Yahia, Oriol Pont, Michel Haissaguerre, Nicolas Derval and Meleze Hocini, “Analysis of Heart Beat Dynamics through Singularity Spectrum”, ICCSE 2011: International Conference on Complex Systems Engineering, Singapore (Accepted). ¾ Harish Kumar, Hussein Yahia and Singh D., “Analysis of MODIS image through the singularity spectrum”, communicated to Geomatrix’12, International Conference on Geospatial Technologies and Applications, India. ¾ Harish Kumar, Hussein Yahia and Singh D., “Empirical Analysis of Multisensor images through the singularity spectrum for land cover classification”, communicated to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. ¾ Harish Kumar, Hussein Yahia, Oriol Pont, Michel Haissaguerre, Nicolas Derval and Meleze Hocini, “Comparative Analysis of Singularity Exponents for the Heart Beat Dynamics”, to be communicated to Journal of Biomedical Informatics. ¾ Harish Kumar, Hussein Yahia, Oriol Pont, Michel Haissaguerre, Nicolas Derval and Meleze Hocini, “A Novel method to distinguish Arrhythmia through MMF”, to be communicated to IEEE Transactions on Biomedical Engineering.

WORK EXPERIENCE Lecturer, in the Department of Computer Science and Engineering, R.V College of Engineering, Bangalore from Feb 2005 to Jul 2005 Research Scholar cum Teaching Assistant, in the Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee from Jul 2005 to September 2010 Post Doctoral Researcher in Team GEOSTAT, INRIA Bordeaux - Sud-Ouest, Talence Cedex, France from Nov 2010 to till-date