Abraham Chandy

Karunya University | KITS · Department of Electronics & Communication Engineering

Spiking neural P systems (SN P Systems) are a class of computational models stimulated by the neural biological systems in which information is processed through spikes and neurons. String languages and functions have been computed using the model of SN P system. Cycle picture language and chain code picture language are two-dimensional picture lan...

COVID-19, a global pandemic has been ravaging the world. The Emergency departments are flooded because of this global pandemic. To provide a good service in the Emergency Departments (ED) in hospitals as a part of smart healthcare, tools that analyze, program, plan or prioritize is required to use the available resources (staff and treatment equipm...

The prior step in most of the kidney related image analysis is precise and authentic kidney segmentation. Although many semi-automated kidney segmentation techniques for 2D ultrasound images have been proposed, only a minimal number of automated techniques were explored. Low contrast and variability in the shape of kidney poses a challenge for the...

The deep learning is a prominent method for automatic detection of COVID-19 disease using medical dataset. This paper aims to give the perspective on the data insufficiency issue that exists in COVID-19 detection associated with deep learning. The extensive study on the available datasets comprising CT and X-ray images are presented in this paper,...

Chronic kidney disease (CKD) is one of the causes of mortality in almost all countries across the globe and the notable thing is its asymptomatic nature in the early stages. This disease is characterized by the gradual loss of kidney function in an individual. Frequently chronic kidney disease is diagnosed based on the Estimated Glomerular Filtrati...

This paper presents a comprehensive review of two major image processing tasks such as restoration and segmentation in the medical field on deep learning perspective. These processes are essential as restoration helps in the removal of noise and segmentation helps in extracting the particular region of interest of an image which is essential for ac...

The data generated in wireless capsule endoscopy during the examination of the gastrointestinal tract is huge and demands large storage and processing time. One of the essential components of the capsule is the compression module that needs to be low power and a low complexity one. This paper aims to bring significant improvement in pre-processing,...

The mathematical study of picture languages (patterns) using generating grammars has its application in pattern recognition and image processing. A pixel picture language is a collection of pixel pictures drawn in a unit square grid using the chain code alphabets {u, d, l, r} with the interpretation of plotting one pixel on the right of the movemen...

Background Fundus photography is an imaging modality exclusively used in ophthalmology for visualizing structures like macula, retina, and optic disc. The fundus camera has only one illumination source, which is situated at its center. Hence, structures away from the center will appear darker than naturally they are. This adverse effect caused by t...

Image processing has paved its way through various applications in the medical field, where researches are being carried out to prompt and improvise the care and treatment given to patients in all aspects. Medical image processing applications concerns the need for obtaining images as per the requirement. Inpainting of markers on medical images gen...

Background: Chronic Kidney Disease is one of the fatal diseases that ultimately result in kidney failure. The threat to mankind is the etiology of chronic kidney disease. Over the years researchers have proposed various techniques and methods to detect and diagnose chronic kidney disease. The traditional method of detecting chronic kidney disease...

The importance of segmentation in medical applications is inevitable and hence its performance and accuracy is a priority. The semi-automated and automated segmentation of kidneys from 2D ultrasound images is quite challenging due to the intensity distribution differences within the kidney and also due to the intensity similarity with the nearby or...

The recently established wireless capsule endoscopy promises itself to be a great advancement in the field of medical diagnosis. The amount of data generated due to a single inspection of gastrointestinal tract is huge, and the transmission demands more cost and power. Due to the inherent nature of the capsule, a low complexity and low-power design...

Background The videos produced during wireless capsule endoscopy have larger data size causing difficulty in transmission with limited bandwidth. The constraint on wireless capsule endoscopy hinders the performance of compression module. Objectives The objectives of this paper are as follows: (i) to have an extensive review on the lossless compres...

The art of restoring the missing pixels or eliminating the unwanted pixels in an image using an appropriate algorithm is called Inpainting. Inpainting is used in wide range of image processing applications. Processing of medical images requires inpainting to remove markers made by the radiologists. The paper proposes a fast and efficient technique...

Wireless capsule endoscopy is a medical diagnostic technique developed for the endoscopic examination of the small bowel. The encoder module is the core of the wireless capsule endoscopic system impacting on power and area requirement for the hardware implementation of the capsule. One of the remarkable features of the endoscopic image is that the...

One of the affordable and least harmful modalities used to efficiently detect and diagnose the kidney diseases is the Ultrasound scans. The main drawback of the ultrasound images is the presence of speckle noise that reduces the efficiency of image processing and hinders the interpretation. This paper proposes a novel technique named Local Binary P...

Object recognition is a challenging task in image processing and computer vision. In this paper, segmentation, feature extraction and classification methods are done for elephant recognition. Thresholding based segmentation technique is used for image segmentation and k-NN classifier is used for object recognition based on the shape features of the...

Content-based image retrieval plays an increasing role in the clinical process for supporting diagnosis. This paper proposes a neighbourhood search method to select the near-optimal feature subsets for the retrieval of mammograms from the Mammographic Image Analysis Society (MIAS) database. The features based on grey level cooccurrence matrix, Daub...

Content-based face image retrieval is an active research area of wide applications. Face image retrieval techniques can be used in applications such as crime prevention, security check, etc. This paper focuses on content-based facial image retrieval based on combination of wavelet transform with dimensionality reduction methods. Reduced feature set...

Object recognition is an important task in image processing and computer vision. This paper aims to include suitable segmentation, feature extraction and classification methods for elephant recognition. Mean-shift filtering is used for image segmentation and k-nn classifier is used for the object recognition based on the shape features of the segme...

Object recognition is a challenging task in image processing and computer vision. This paper proposes a clustering-based image segmentation approach for elephant recognition. An appreciable recognition rate was achieved by κ-means clustering technique followed by feature extraction and Κ nearest neighbour (Κ-NN) classifier. The κ-means clustering a...

Texture is one of the visual contents of an image used in content-based image retrieval (CBIR) to represent and index the image. Statistical textural representation methods characterize texture by the statistical distribution of the image intensity. This paper proposes a gray level statistical matrix from which four statistical texture features are...

Content-based image retrieval (CBIR) is an active research area over the past few decades. In medical applications like mammogram analysis content based image retrieval techniques helps the radiologists or physicians to access similar images from a large medical database to aid diagnosis. In this paper content-based retrieval of mammograms from DDS...

This paper aims to develop an efficient content - based image retrieval approach for brain image database. The combination of Cohen-Daubechies-Feauveau (CDF) 9/7 wavelet and Local Ternary Co-occurrence Patterns (LTCoP) is used for feature extraction in solving the brain image retrieval problem. The experimental dataset used for the retrievalpurpose...

Mammogram retrieval systems and techniques have a key role in supporting the radiologists and physicians in their decision making. This paper presents an approach based on the biorthogonal wavelet and decision tree methods for the retrieval of mammograms from digital database for screening mammogram (DDSM) database. Classification and regression tr...

This paper proposes a clustering based image segmentation approach for elephant recognition. Appreciable recognition rate was achieved by k-means clustering technique followed by feature extraction and K nearest neighbour (K-NN) classifier. The k-means algorithm employs the concept of fitness and belongingness to provide a more adaptive andbettercl...

Video copy detection is an active research area as copyright issues continue to be a challenge to the multimedia industry. A content-based video copy detection method using discrete wavelet transform is presented here. Daubechies wavelet transform is used to obtain feature descriptor from video frames. The computation required for similarity search...

The increase in availability of music information demands for the development of tools for audio retrieval. Audio information retrieval implicates the retrieval of similar audio files based on the feature. Feature extraction is one of the important tasks where the entire retrieval system relies on. In this work, audio information retrieval has been...

Content-based image retrieval methods aid physicians in diagnosing the early detection of diabetic retinopathy for preventing blindness. In this work, the combination of two dimensional dual-tree complex wavelet transform (DT-CWT) and generalized Gaussian density (GGD) model is used for feature extraction. Kull-back Leibler Divergence (KLD) compute...