Person: Roy, Anil
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Anil Roy
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079-68261613
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Applications of Image Processing, Fiber Optics and Optical Communication, High speed Semiconductor Devices, Nanoscience and Nanotechnology, Quantum Optics, Technologies for Humanitarian Challenges.
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I am a faculty of DA-IICT, Gandhinagar (India) and am an alumnus of IIT Delhi and IIT Roorkee. I obtained my PhD degree in Physics from IIT Delhi in 1993. Prior to joining DA-IICT in 2003, I worked at Centre for Theoretical Studies at Indian Institute of Science, Bangalore (India) during 1993-94 followed by the Optical Fiber Group at IIT Delhi (India) till 1996. My main academic interest areas are sensors, Internet of Things, image processing, fiber optics, semiconductor physics, applications of technologies for humanitarian challenges.
I am a senior member of IEEE, a member of Optica (formerly Optical Society of America) and a member of Optical Society of India. After serving two terms as VP Technical Operations (2020-2023), I am currently the President-elect of IEEE Sensors Council (2024-2025). I was also the Chair of IEEE Conference Publications Committee (2019-2020). I have been the General co-Chair of many international conferences, such as
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13 results
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Publication Metadata only Optimized Wishart Network for an Efficient Classification of Multifrequency PolSAR Data(IEEE, 01-11-2018) Gadhiya, Tushar; Roy, Anil; Roy, Anil; DA-IICT, Gandhinagar; Gadhiya, Tushar (201621009)Publication Metadata only Keypoint based comprehensive copy-move forgery detection(IET, 01-12-2021) Diwan, Anjali; Sharma, Rajat; Mitra, Suman; Mitra, Suman; Mitra, Suman; Roy, Anil; Roy, Anil; DA-IICT, Gandhinagar; Diwan, Anjali (201521013); Sharma, Rajat (201811045)Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy-move forgery. In copy-move forgery copied portion of the image is pasted on another part of the same image. Geometrical transformations are used on the copied portions of the image before pasting it for the tampered image to look realistic and visually convincing. To make it more complex, other processing approaches may also be applied in the forged region for hiding traces of forgery. These processings are the scale, rotation, JPEG compression, and AWGN. In this paper, an approach based on features of the CenSurE keypoint detector and FREAK descriptor is proposed. This combination has novelty in itself as it has never been used for this purpose before to the best of authors' literature studies. CenSurE detectors are fast and give stable and accurate output even in the case of rotated images, which we club with binary descriptor FREAK. Hierarchical clustering and Neighbourhood search is applied in such a way that it can locate and detect multiple copy-move forgeries. The authors are hopeful that the proposed approach may be used in real-time image authentication and copy-move forgery detection.Publication Metadata only Experimental Investigation of Leaf Wetness Sensing Properties of MoS2 Nanoflowers-Based Flexible Leaf Wetness Sensor(IEEE, 01-02-2023) Khaparde, Priyanka; Patle, Kamlesh S; Agrawal, Yash; Borkar, Hitesh; Palaparthy, Vinay; Gangwar, Jitendra; Roy, Anil; Agrawal, Yash; Palaparthy, Vinay; Roy, Anil; Patle, Kamlesh S (202121017)To abate crop loss, it is important to explore the plant disease management systems, where leaf wetness sensors (LWS) are widely used. The leaf wetness duration (LWD) extracted from the LWS is related to plant diseases. In this work, we have fabricated the LWS on the polyamide flexible substrate where Molybdenum disulfide (MoS2) is used as the sensing film to explore the leaf wetness sensing mechanism. Further, we have passivated the MoS2�with the help of acrylic protective lacquer (APL) conformal coating (MoS2�+ APL), which reduce the interaction of the water molecules with the sensor. Lab measurements indicated that fabricated LWS on the flexible substrate with MoS2�and MoS2�+ APL as the sensing film offers a response of about ? 40 000% and ? 250%, respectively, at 500 Hz excitation frequency when the entire sensing area is filled with the water molecule. The response time of the MoS2�and APL-coated flexible sensor is about 180 s. Fabricated LWS sensors offer hysteresis of about � 4% in wetness. Further, we have identified that oxidation of the sulphur in the MoS2�plays an important role in the leaf wetness sensing mechanism. Furthermore, we understood that MoS2�when passivated with APL coating, the oxidation effect is reduced and the sensor response is negligible.Publication Metadata only CSD Type Family Solar Drying Technology and its Potential Impact on Rural Development and Nutrition - a Case Study(CCSE, 01-04-2014) Sinha, Sangeeta; Singh, SNP; Roy, Anil; Roy, Anil; DA-IICT, GandhinagarGlobalization has adversely affected development of rural areas in developing countries. Rural areas are unable to absorb new technologies due to low literacy rates. Local Products, mostly from agricultural produces, are increasingly replaced by cheaper products from organized mechanized farming from one or the other corner of the globe. In this paper, family type cabinet solar dryer designs are presented in commensuration with the contemporary requirement of rural Bihar. Design objective includes simplification of technology and process, easy maintenance and low price to dry exotic produces which has significant export potential. Field trials are conducted, social surveys are undertaken and nutritional values of the products are determined in actual condition. Results indicate that simpler technology with state-of-art control of temperature by a combination of high heat capacity material and phase change material is most suitable to dry vegetables and spices, commonly called �Cash Crops�. Their nutritional values remain within 80% limits even after six months. The technology is appropriate as it uses local materials; sustainable as it is cost-effective and employment generating ability and; robust as it uses very simple way for controlled drying.Publication Metadata only Superpixel-Driven Optimized Wishart Network for Fast PolSAR Image Classification Using Global k-Means Algorithm(IEEE, 01-01-2020) Gadhiya, Tushar; Roy, Anil; Roy, Anil; DA-IICT, GandhinagarLimitation of optical remote sensing technology gave rise to synthetic aperture radar (SAR) imaging. SAR is a microwave imaging technique, which promises to have a long-range propagation characteristic allowing imaging under harsh weather conditions or in hostile lighting situation. This has opened up a domain of classification using polarimetric SAR (PolSAR) images. In this article, we propose a fast PolSAR image classification algorithm, which uses not only pixel-based feature but also spatial features around each pixel. This is achieved by introducing superpixel-driven optimized Wishart network. The first improvement suggested in this article is to take advantage of a fast global k-means algorithm for obtaining optimal cluster centers within each class. It uses real-valued vector representation of PolSAR coherency matrix along with fast matrix inverse and determinant algorithms to reduce computational overhead. Our method then exploits the information of neighboring pixels by forming a superpixel so that even a noisy pixel may not be assigned a wrong class label. The proposed network uses dual-branch architecture to efficiently combine pixel and superpixel features. We concluded that our proposed method has better efficiency in terms of classification accuracy and computational overhead compared with other deep learning-based methods available in the literature.Publication Metadata only A novel method for detecting light source for digital images forensic(De Gruyter, 01-06-2011) Agrawal, Rohin; Mitra, Suman; Mitra, Suman; Mitra, Suman; Roy, Anil; Roy, Anil; DA-IICT, Gandhinagar; Agrawal, Rohin (200501187)Manipulation in image has been in practice since centuries. These manipulated images are intended to alter facts � facts of ethics, morality, politics, sex, celebrity or chaos. Image forensic science is used to detect these manipulations in a digital image. There are several standard ways to analyze an image for manipulation. Each one has some limitation. Also very rarely any method tried to capitalize on the way image was taken by the camera. We propose a new method that is based on light and its shade as light and shade are the fundamental input resources that may carry all the information of the image. The proposed method measures the direction of light source and uses the light based technique for identification of any intentional partial manipulation in the said digital image. The method is tested for known manipulated images to correctly identify the light sources. The light source of an image is measured in terms of angle. The experimental results show the robustness of the methodology. Keywordsimage forensics�manipulation�least square approximation�surface normals�decorrelation�noise filterPublication Metadata only Evolution of Dew and Rain Water Resources in Gujarat (India) between 2005 and 2021(Preprint.org, 24-06-2024) Budhbhatti, Rupal; Muselli, Marc; Beysens, Daniel; Roy, Anil; Roy, Anil; DA-IICT, GandhinagarGlobal warming leads in general to a reduction in precipitations and non-rainfall water contributions such as dew. The present study, carried out in Gujarat (India) for 17 years between 2005 and 2021, shows however a rare increase of the rain falls and dew condensation, the latter related to an increase in relative humidity and a decrease in wind amplitudes. Rain was obtained from meteo stations. Dew was calculated from an energy model and meteo data from 15 meteo stations (14 in India and 1 in Pakistan) and compared to early and dedicated measurements in 13 sites. Maps of dew, rain and their relative contributions during the period are provided. They show that, while rain mainly occurs during the monsoon (June to September), dew forms during the dry season (October to April). This water resource was mapped over the Gujarat state of India by using a kriging process. According to the site, the dew/rain ratios can represent between 4.6% (Ahmedabad) to 37.2% (Jamnagar) on the whole period of 17 years. This positive evolution, which is observed since 2015-2017, is likely to continue in the future.Publication Metadata only CNN-Keypoint Based Two-Stage Hybrid Approach for Copy-Move Forgery Detection(IEEE, 21-03-2024) Diwan, Anjali; Roy, Anil; Roy, Anil; DA-IICT, GandhinagarAuthenticating digital images poses a significant challenge due to the widespread use of image forgery techniques, including copy-move forgery. Copy-move forgery involves copying and pasting portions of an image within the same image while applying geometric transformations to make the forged image appear genuine. Furthermore, additional processing techniques such as additive noise scaling, JPEG compression, and rotation can be employed to further conceal evidence of forgery. These factors contribute to the complexity of detecting and verifying the authenticity of digital images. The proposed work uses a combination of the CenSurE keypoint detection and a CNN architecture to detect and localize copy-move forgery in digital images. The use of CNN architecture allows the algorithm to update its learning via training data repeatedly, making it a data-driven approach. By combining keypoints with CNN features, the proposed approach can enhance the detection of copy-move forgery even in the presence of attacks such as geometrical transformations, scale, and rotation. Additionally, the proposed approach can effectively handle post-processing operations such as JPEG compression, additive noise, image blur, colour reduction, brightness change, and contrast adjustment. One important aspect of the proposed approach is its ability to handle images with different textures, including smooth and self-similar structural images with dense textures. The proposed approach can produce stable results in images with various attacks, making it a functional and reliable tool for detecting copy-move forgery in a diverse range of forged images. The proposed approach represents an important contribution to the field of multimedia forensics, providing an effective and reliable means of detecting and localizing copy-move forgery in digital images.Publication Metadata only Dew plant for bottling water(Elsevier, 01-07-2017) Sharan, Girja; Roy, Anil; Royon, Laurent; Mongruel, Anne; Beysens, Daniel; DA-IICT, GandhinagarIn a context of�climate change�and increasing need of fresh water in the world, rain and dew water can have a significant impact as new sources of water, especially in arid and semi-arid areas. The aim of the paper is to demonstrate that atmospheric moisture can be harvested and processed into safe�drinking water�comparable in quality and price to�reverse osmosis�processed water available in the market. The paper describes the construction and functioning of a water production plant in northwest India (Kothara). Rain and dew are collected; for dew special attention has to be taken. In particular, special condenser architecture (ridges) is designed using�Computational Fluid Dynamics simulation�and improved condensing surfaces are operated. Dew yields are estimated from the meteo data and using simulation. From the figures an economic model is derived; it comes out that water passively harvested from atmospheric moisture may be cheaper than that from�reverse osmosis�and does not pollute the environment, supporting the importance of dew and rain resources to provide supplementary supply of potable water in arid and semi-arid environment.Publication Metadata only Fractional Derivative Based TVD Smoothening and Baseline Correction for Extracting Leaf Wetness Duration From LW Sensor: A Novel Approach(IEEE, 28-11-2023) Agrawal, Yash; Gupta, Samaksh; Roy, Anil; Palaparthy, Vinay; Kumar, AhladOne of the driving factors leading to the modernization in the agriculture sector is the era of sensors-driven technologies. Annually, as reported by the Associated Chambers of Commerce and Industry of India, $500 billion of crops are lost due to pests and plant diseases in a country like India, where at least 200 million Indians go to bed hungry every night. For the detection of plant disease, the measurement of leaf wetness duration (LWD) values becomes a crucial step. This requirement of measuring LWD values led to the development of an in situ IoT-enabled LW sensor earlier. The same LW sensor was deployed for about four months, and data for the same were collected. Furthermore, for extracting LWD information, smoothing algorithms like total variation denoising (TVD) are applied. However, our novelty lies in introducing the order of fractional derivative (?) in an already existing TVD algorithm, which is varied from 1 to 2, and results are found to be satisfying. To get an effective baseline, we combined this algorithm with three baseline correction techniques: asymmetric least squares, improved asymmetric least squares, and asymmetrically reweighted penalized least squares (arPLS). The optimal range of ? lies in the range of 1.6 to 2 for getting the highest accuracy. This study demonstrates that our novel approach of integrating fractional derivatives into an existing TVD algorithm enhances its performance in identifying Leaf wetness events. The highest accuracy (i.e., the highest number of events detected) of 0.80 is found by total variation smoothing with the arPLS baseline correction technique.