Mukesh Saraswat

Jaypee Institute of Information Technology | JIIT · Department of Computer Science & IT

In the common classification practices, feature selection is an important aspect that highly impacts the computation efficacy of the model, while implementing complex computer vision tasks. The metaheuristic optimization algorithms gain popularity to obtain optimal feature subset. However, the feature selection using metaheuristics suffers from two...

Wireless sensor network has several constraints. The major constraint is the limited energy resource of the sensor nodes, limiting the overall efficiency and lifetime of the network system. Clustering is a widely used strategy that arranges the network into smaller groups called clusters for improving the performance and longevity of the network. T...

Over the last decades, there has been a revolution in the analysis of medical images with the new technological advancements. Innovative intelligent technologies have been developed to analyze and interpret medical images automatically for diseases diagnosis and disease assessment and for combatting new diseases. This new volume explores the lates...

Segmentation of vehicles into images of road traffic with congested and unstructured traffic patterns is a challenging task. For the same, this paper presents a modified-UNet which segments the input image by the sequential encoding and decoding steps. The modified-UNet uses a number of convolutions, inception modules, and batch normalization to en...

In a watermarking scheme, high embedding capacity and robust recovery is a challenging issue. The existing watermarking schemes embed either a binary or grayscale watermark in the luminance component of the color image, which influences the imperceptibility. Moreover, current schemes are lack of robustness against numerous image processing attacks....

The exponential growing demand for computer-aided systems has significantly increased the detection of cancerous cells from digital histopathology images. However, the cell manual sectioning and color variation inevitably create challenges and affect the performance of computer-assisted diagnosis (CAD) due to misclassification. Therefore, color nor...

The vehicle segmentation in the images of a crowded and unstructured road traffic, having inconsistent driving patterns and vivid attributes like colour, shapes, and size, is a complex task. For the same, this paper presents a new firefly algorithm-based superpixel clustering method for vehicle segmentation. The proposed method introduces a modifie...

The progress in digital histopathology for computer-aided diagnosis leads to advancement in automated histopathological image classification system. However, heterogeneity and complexity in structural background make it a challenging process. Therefore, this paper introduces robust and reliable new bag-of-feature framework. The optimal visual words...

Automatic image segmentation is a challenging task in computer vision applications, especially in the presence of occluded objects, varying color, and different lighting conditions. The advancement of depth-sensing technologies has introduced RGB-Depth cameras which are capable to generate RGB-Depth images and brought significant changes in compute...

In Industrial Internet-of-Things, data streams across heterogeneous networks which results in several cyber–physical attacks. Moreover, the security of unlabeled data is a challenging task. For the same, this paper presents a new clustering method for intrusion detection. The proposed method employs a novel variant of gravitational search algorithm...

Automated medical imagining is growing rapidly for advanced clinical treatment and intervention in medical diagnosis. The segmentation of nuclei in digital histopathology is considered the most crucial aspect in diagnosis and evaluating the severity of disease. Therefore, in this paper, an automated nuclei segmentation method has been introduced fo...

During the last decade, an exponential development has been observed in the field of intelligent vision technologies. These have shown profound success in a wide range of application domains such as robotics, bio-metric identification, intruder detection, health care, agriculture, and many more. With advancement in vision technologies, medical diag...

The popularity of digital histopathology is growing rapidly in the development of computer aided disease diagnosis systems. However, the color variations due to manual cell sectioning and stain concentration make the process challenging in various digital pathological image analysis such as histopathological image segmentation and classification. H...

Image segmentation partitions an image into coherent and non-overlapping regions. Due to variations of visual patterns in images, it is a challenging problem. This paper introduces a new superpixel-based clustering method to efficiently perform the image segmentation. In the proposed method, initially superpixels from an image are obtained. The sup...

Meta-heuristic methods have been successfully applied in many real-world optimization problems. Recently, Henry gas solubility optimization algorithm has been introduced which is based on Henry’s law. To improve its solution precision, a new chaotic Henry gas solubility optimization method has been presented in this paper. The proposed variant is v...

This book is a collection of selected papers presented at the First Congress on Intelligent Systems (CIS 2020), held in New Delhi, India, during September 5–6, 2020. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers selected papers in the area of computer vision....

The automatedSaraswat, Mukesh methods for the categorization of the histopathological images is very useful in disease diagnosis and prognosis.Pal, Raju However, due to complex image background and morphological variations these images generate very large feature vectors which make the automated classification task difficult.Singh, Roop Therefore,M...

Agriculture is the main source of human habitation and its redemption from disease is a primary concern for any economy. For the same, computer vision techniques have been proven to be quite useful. However, the diseased plant identification is still a challenging task due to the disparity in the leaf images. To alleviate the same, this chapter pro...

Image segmentation is an essential phase of computer vision in which useful information is extracted from an image that can range from finding objects while moving across a room to detect abnormalities in a medical image. As image pixels are generally unlabelled, the commonly used approach for the same is clustering. This paper reviews various exis...

An efficient classification method to categorize histopathological images is a challenging research problem. In this paper, an improved bag-of-features approach is presented as an efficient image classification method. In bag-of-features, a large number of keypoints are extracted from histopathological images that increases the computational cost o...

This book is a collection of best selected high-quality research papers presented at the International Conference on Advances in Energy Management (ICAEM 2019) organized by the Department of Electrical Engineering, Jodhpur Institute of Engineering & Technology (JIET), Jodhpur, India, during 20–21 December 2019. The book discusses intelligent energy...

This book is a collection of selected papers presented at the First Congress on Intelligent Systems (CIS 2020), held in New Delhi, India during September 5 – 6, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers topics such as Internet of Things, information...

Determining the correct number of clusters is essential for efficient clustering and cluster validity indices are widely used for the same. Generally, the effectiveness of a cluster validity index relies on two factors: (i) separation, defined by the distance between a pair of cluster centroids or a pair of data points belonging to different cluste...

Digital watermarking embeds a watermark to minimise the problem of illegal copying and disseminating multimedia contents. However, the existing techniques do not maintain the imperceptibility and robustness simultaneously. To achieve the same, this study proposes an optimised robust watermarking technique using chaotic kbest gravitational search al...

Feature selection is one of the key components of data mining and machine learning domain that selects the best subset of features with respect to target data by removing irrelevant data. However, it is a complex task to select optimal set of features from a dataset using traditional feature selection methods, as for n number of features, \(2^n\) f...

Automated histopathological image analysis is a challenging problem due to the complex morphological structure of histopathology images. Bag-of-features is one of the prominent image representation methods which has been successfully applied in histopathological image analysis. There are four phases in the bag-of-features method, namely feature ext...

The histopathological image classification is a vivid application for medical diagnosis and neural network has been successful in the image classification task. However, finding the optimal values of the neural network is still a challenging task. To accomplish the same, this paper considers a two-layer neural network which is optimized through int...

Software testing is a systematic process to identify the presence of errors in the developed software performed using test data. Manually generating test data is ineffective in terms of cost, time and code coverage. Past three decades automation of test data generation has been a research problem of interest and a wide range of work has been done t...

An exponential growth of histopathological digital images over the Internet requires an efficient method for organizing them properly for better retrieval and analysis process. For the same, an automatic histopathological image classification system can be useful. Moreover, such classification system may also be used to identify the inflamed and he...

The automated quantification of different cell structures available in histopathological images is a challenging task due to the presence of complex background structures. Moreover, the tissues of different categories, namely epithelium tissue, connective tissue, muscular tissue, and nervous tissue have heterogeneous structure which limits the appl...

A reliable nuclei segmentation is still an open-ended problem, especially in the breast cancer histology images. For the same, this paper proposes an intelligent gravitational search algorithm based superpixel clustering method for automatic nuclei segmentation. In the proposed method, a novel variant of gravitational search algorithm, intelligent...

Background: With the expeditious development of current medical imaging technology, the availability of histopathological images has been increased in a large number. Hence, histopathological image classification and annotation have emerged as the prime research fields in the pathological diagnosis and clinical practices. Several methods are availa...

Bag of features is an efficacious method for image classification. However, its applicability on histopathological images is still an open ended research problem. In this paper, a novel bag of features based histopathological image classification method is presented. The proposed method involves three steps: (i) Feature extraction using AlexNet, (i...

Matlab code for the paper: An optimum multi-level image thresholding segmentation using non-local means 2D histogram and exponential Kbest gravitational search algorithm

Multi-level image thresholding segmentation divides an image into multiple non-overlapping regions. This paper presents a novel two-dimensional (2D) histogram-based segmentation method to improve the efficiency of multi-level image thresholding segmentation. In the proposed method, a new non-local means 2D histogram and a novel variant of gravitati...

The automatic categorization of histology images for medical diagnosis is a prime application area. The bag-of-features method is a popular method for the automatic image categorization. However, due to the complex background structures of histology images, it is a tedious task to quantify such images using the bag-of-features method. Therefore, a...

Data clustering is one of the important tool in data analysis which partitions the dataset into different groups based on similarity and dissimilar-ity measures. Clustering is still a NP-hard problem for large dataset due to the presence of irrelevant, overlapping, missing and unknown features which leads to converge it into local optima. Therefore...

Biogeography-based optimization (BBO) is one of the popular evolutionary algorithms, inspired by the theory of island biogeography. It has been successfully applied in various real world optimization problems such as image segmentation, data clustering, combinatorial problems, and many more. BBO finds the optimal solution by using two of its main o...

Data clustering is one of the important tool in data analysis which partitions the dataset into different groups based on similarity and dissimilarity measures. Clustering is still a NP-hard problem for large dataset due to the presence of irrelevant, overlapping, missing and unknown features which leads to converge it into local optima. Therefore,...

Sentiment analysis is one of the prominent fields of data mining that deals with the identification and analysis of sentimental contents generally available at social media. Twitter is one of such social medias used by many users about some topics in the form of tweets. These tweets can be analyzed to find the viewpoints and sentiments of the users...

This post contain the MATLAB code for simulating WSN clustering based on Biogeography-based Optimization. Call start.m file to start the simulation. Ref: Pal, Raju, Himashu Mittal, Avinash Pandey, and Mukesh Saraswat. "BEECP: Biogeography optimization-based energy efficient clustering protocol for HWSNs." In Contemporary Computing (IC3), 2016 Ni...

Physical and chemical properties of protein help to determine the quality of protein structure. Here we explore the machine learning models using six physical and chemical properties, namely total empirical energy, secondary structure penalty, total surface area, pair number, residue length and Euclidean distance to predict the RMSD of a protein st...

A robust and high quality image watermarking method has high demand for protection of multimedia data over internet. The existing image watermarking methods generally exploit the correlated color models due to which only one color component at a time can be used for embedding the watermark. Therefore, in this paper, a novel steerable pyramid transf...

An automatic segmentation of leukocytes can assist pharmaceutical companies to take decisions in the discovery of drug and encourages for development of automated leukocytes recognition system. Segmentation of leukocytes in tissue images is a complex process due to the presence of various noise effects, large variability in the images, and shape of...

The exponential growths in electronic data over internet have increase the demand of a robust and high quality watermarking method for authentication and copyright protection. The available digital image watermarking methods generally use the correlated color spaces which impose the limitations to researchers for using only one color component at a...

The exponential growth in electronic data over internet have increased the demand of a robust and high quality watermarking method for authentication and copyright protection. In general, the existing digital image watermarking methods embed the binary or gray scale watermark into the host image although most multimedia images are available in colo...

In automatic segmentation of leukocytes from the complex morphological background of tissue section images, a vast number of artifacts/noise are also extracted causing large amount of multivariate data generation. This multivariate data degrades the performance of a classifier to discriminate between leukocytes and artifacts/noise. However, the sel...

Automatic quantification and classification of leukocytes in microscopic images are of paramount importance in the perspective of disease identification, its progress and drugs development. Extracting numerical values of leukocytes from microscopic images of blood or tissue sections represents a tricky challenge. Research efforts in quantification...

Automated leukocytes segmentation in skin section images can be utilized by various researchers in animal experimentation for testing anti-inflammatory drugs and estimating dermatotoxicity of various toxic agents. However, complex morphological structure of skin section degrades the performance of leukocytes segmentation due to the extraction of va...

Colour transfer is a prime area of research in image processing in recent years. In many real-life image applications, colour transfer of the image is required. A few methods have been developed to alter the colour appearance of the images as per the colour information of the reference image. Histopathological image analysis is one of the applicati...

An automatic segmentation of leukocytes can assist pharmaceutical companies to take decisions in the discovery of drugs and encourages for development of automated leukocyte recognition system. Segmentation of leukocytes in tissue images is a complex process due to the presence of various noise effects, large variability in the images and shape of...

Automated leukocyte classification can assist histopathologist for quantifying inflammatory cells in microscopic images. Most of the work for classification of leukocytes have been done on blood smear or immunohistochemically (IHC) stained or immunofluroscence (IF) stained tissue section images. But rare work have been initiated till date to automa...

Video is one of the most commonly used multimedia data used in daily life. This increases the occurrences of abuse and copyright infringement which happen to video data content. To overcome from this problem video security and copyright protection techniques are required. Video watermarking is one of the most popular techniques for the providing se...

India is an agricultural country where large number of human beings are involved in cropping different plants for their living. But these plants may be affected by different diseases which are to be handled by the farmers within time to increase their productivity. An automatic plant disease identification system can be helpful for the farmers to i...

Sign Language is one of the prime applications of facial expression recognition system. It is an easy task for a human being to identify the expression of a person in a particular image sequence but not many efficient fully automated systems are available to perform this task. Lot of work has been done to automate the recognition system for many si...

Particle Swarm Optimization is a popular heuristic search algorithm which is inspired by the social learning of birds or fishes. It is a swarm intelligence technique for optimization developed by Eberhart and Kennedy [1] in 1995. Inertia weight is an important parameter in PSO, which significantly affects the convergence and exploration-exploitatio...

Detection of landmarks in a face is very crucial in facial expression recognition system. It is an easy task for a human being to identify the expression of a person in a particular video sequence but not many efficient fully automated systems are available to perform this task. Face recognition requires the detection of face followed by landmarks...