Sheli Sinha Chaudhuri

Work place: ETCE Department, Jadavpur University, India



Research Interests: Image Processing, Multimedia Information System, Mathematics of Computing


Dr. Sheli Sinha Chaudhuri is an Associate Professor at ETCE Department of Jaduvpur University. She completed her B-Tech, M-Tech, and PhD at Jaduvpur University. She has a vast teaching experience of fourteen years. She has large number of papers in International and national level journals as well as conferences. Currently research scholars are pursuing PhD under her guidance. She is the member of IEEE and IEI.

Author Articles
Modeling of Haze Image as Ill-Posed Inverse Problem & its Solution

By Sangita Roy Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 Dec. 2016

Visibility Improvement is a great challenge in early vision. Numerous methods have been experimented. As the subject is random and different significant parameters are involved to improve the vision, it becomes difficult, sometimes unsolvable. In the process original image has to be retrieved back from a degraded version of the image which is often difficult to perceive. Thus the problem becomes ill-posed Inverse Problem. This has been observed that VI (Visibility Improvement) is associated with haze and blur. This complex nature requires probability distribution, estimation, airlight calculation etc. In this paper a combination of haze and blur model has been proposed with detail discussions.

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Error Measurement & its Impact on Bilateral - Canny Edge Detector-A Hybrid Filter

By Sangita Roy Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 Feb. 2016

Image Processing, a subset of Computer Vision, is an important branch in modern technology. Edge detection is a subset of segmentation to detect object of interest. Different image edge detection filters and their evaluating parameters are introducing rapidly. But the performance of an edge detector is an open problem. In this paper different performance measures of edge detection have been discussed in details and their application on a hybrid filter using Bilateral and Canny is proposed. Its parametric performance has been evaluated and other well established or classical existing edge detecting filters have been compared with it to measure its efficiency.

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Nature-Inspired Swarm Intelligence and Its Applications

By Sangita Roy Samir Biswas Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 Dec. 2014

In 1989 Gerardo Beni and Jing Wang first proposed the name “Swarm Intelligence” in their paper “Swarm Intelligence in Cellular Robotic Systems”. Some remarkable observations of different researchers are studied in this paper, like the proximity principle, the quality principle, the principle of diverse response, the principle of stability, the principle of adaptability. To enhance the capabilities of robot and different systems, researchers started to exploit the behavior of natural systems. Swarm groups are governed by three rules, move in the same direction as your neighbor, remain close to your neighbor, and avoid collision with your neighbor .Characteristics of swarm groups are emergence and stigmergy. Different insects like ants, wasps, termites carry out a work locally for global goal with sufficient flexibility as they are not controlled centrally. In this paper the existing research works are analysed to show the behavior in social insects by using self-organization, positive feedback, negative feedback, amplification of fluctuation, multiple interactions. It has also been observed that these insects are almost blind and memoryless, still they communicate indirectly among themselves for stigmergic effect by using pheromone. Implementation of swarm intelligence in robotics i.e., swarm robots are narrated. The limitations of swarm robots as well as factors behind the success of swarm robotics have also been encompassed. Finally authors focus on swarm robots applications in telecommunication fields, civil engineering and digital image processing.

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Cuckoo Search Algorithm using Lèvy Flight: A Review

By Sangita Roy Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 Dec. 2013

Cuckoo Search (CS) is a new met heuristic algorithm. It is being used for solving optimization problem. It was developed in 2009 by Xin- She Yang and Susah Deb. Uniqueness of this algorithm is the obligatory brood parasitism behavior of some cuckoo species along with the Levy Flight behavior of some birds and fruit flies. Cuckoo Hashing to Modified CS have also been discussed in this paper. CS is also validated using some test functions. After that CS performance is compared with those of GAs and PSO. It has been shown that CS is superior with respect to GAs and PSO. At last, the effect of the experimental results are discussed and proposed for future research.

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Bio-inspired Ant Algorithms: A review

By Sangita Roy Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 Apr. 2013

Ant Algorithms are techniques for optimizing which were coined in the early 1990’s by M. Dorigo. The techniques were inspired by the foraging behavior of real ants in the nature. The focus of ant algorithms is to find approximate optimized problem solutions using artificial ants and their indirect decentralized communications using synthetic pheromones. In this paper, at first ant algorithms are described in details, then transforms to computational optimization techniques: the ACO metaheuristics and developed ACO algorithms. A comparative study of ant algorithms also carried out, followed by past and present trends in AAs applications. Future prospect in AAs also covered in this paper. Finally a comparison between AAs with well-established machine learning techniques were focused, so that combining with machine learning techniques hybrid, robust, novel algorithms could be produces for outstanding result in future.

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Analysis of P-QRS-T Components Modified by Blind Watermarking Technique Within the Electrocardiogram Signal for Authentication in Wireless Telecardiology Using DWT

By Nilanjan Dey Sayantan Mukhopadhyay Achintya Das Sheli Sinha Chaudhuri

DOI:, Pub. Date: 28 Jul. 2012

Presently considerable amount of work has been done in tele-monitoring which involves the transmission of bio-signals and medical images in the wireless media. Intelligent exchange of bio-signals amongst hospitals needs efficient and reliable transmission. Watermarking adds “ownership” information in multimedia contents to prove the authenticity, to verify signal integrity, or to achieve control over the copy process. This paper proposes a novel session based blind watermarking method with secret key by embedding binary watermark image into (Electrocardiogram) ECG signal. The ECG signal is a sensitive diagnostic tool that is used to detect various cardio-vascular diseases by measuring and recording the electrical activity of the heart in exquisite detail. The first part of this paper proposes a multi-resolution wavelet transform based system for detection ‘P’,‘Q’,‘R’,‘S’,‘T’ peaks complex from original ECG signal of human being. ‘R-R’ time lapse is an important component of the ECG signal that corresponds to the heartbeat of the concerned person. Abrupt increase in height of the ‘R’ wave or changes in the measurement of the ‘R-R’ interval denote various disorders of human heart. Similarly ‘P-P’, ‘Q-Q’, ‘S-S’, ‘T-T’ intervals also correspond to different disorders of heart and their peak amplitude envisages other cardiac diseases. In this proposed method the ‘P Q R S T’-peaks are marked and stored over the entire signal and the time interval between two consecutive ‘R’-peaks and other peaks interval are measured to detect anomalies in behavior of heart, if any. The peaks are achieved by the composition of Daubechies sub-bands wavelet of original ECG signal. The accuracy of the P, QRS and T components detection and interval measurement is achieved with high accuracy by processing and thresholding the original ECG signal. The second part of the paper proposes a Discrete Wavelet Transformation (DWT) and Spread Spectrum based watermarking technique. In this approach, the generated watermarked signal having an acceptable level of imperceptibility and distortion is compared to the Original ECG signal. Finally, a comparative study is done for the intervals of two consecutive ‘R-R’ peaks, ‘P-R’, ‘Q-T’, ‘QTc’, QRS duration, cardiac output between original P, QRS and T components detected ECG signal and the watermarked P,QRS and T components detected ECG signal.

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Fuzzy Logic Based Four Step Search Algorithm for Motion Vector Estimation

By Suvojit Acharjee Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 May 2012

Visual information is very much important for human to perceive, recognize and understand the surrounding world. As we live in the age of multimedia video sequences are very useful to us for providing information. Video involves a huge amount of data. So video compression is necessary Motion compensation has lot of computation in total video compression process. Fast motion vector estimation is a key-factor in video coding standard. Full search algorithm is the best algorithm between all the block matching algorithms to estimate the motion vector estimation with a huge computation cost. The challenge is to reduce the computational complexity of Full Search algorithm without losing too much quality at the output.
In this paper we propose to implement the fuzzy logic based Four Step Search algorithm which performs better than other block matching algorithms.

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Fuzzy Logic Based Three Step Search Algorithm for Motion Vector Estimation

By Suvojit Acharjee Sheli Sinha Chaudhuri

DOI:, Pub. Date: 8 Mar. 2012

Motion compensation process is the most computationally expensive operation in the entire video compression process. Fast motion estimation technique plays a very important role in video compression standard. In Block Matching Algorithm Full Search Algorithm produces the best result for motion vector estimation. But Full Search algorithm is a time consuming and computationally expensive process. The Challenge is to reduce the computational complexity of Full Search algorithm without losing too much quality at the output.
In this paper we propose to implement the fuzzy logic based Three Step Search algorithm. This Algorithm performs better than the Three Step Search(TSS), New Three Step Search(NTSS), Four Step Search(FSS) algorithm.

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