Pawanesh Abrol

University of Jammu, Jammu, Jammu and Kashmir, India, Department of Computer Science and IT, Faculty Member

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Papers by Pawanesh Abrol

Automatic text extraction and character segmentation using maximally stable extremal regions

by nitigya sambyal and Pawanesh Abrol

Text detection and segmentation is an important prerequisite for many content based image analysi... more Text detection and segmentation is an important prerequisite for many content based image analysis tasks. The paper proposes a novel text extraction and character segmentation algorithm using Maximally Stable Extremal Regions as basic letter candidates. These regions are then subjected to thresholding and thereafter various connected components are determined to identify separate characters. The algorithm is tested along a set of various JPEG, PNG and BMP images over four different character sets; English, Russian, Hindi and Urdu. The algorithm gives good results for English and Russian character set; however character segmentation in Urdu and Hindi language is not much accurate. The algorithm is simple, efficient, involves no overhead as required in training and gives good results for even low quality images. The paper also proposes various challenges in text extraction and segmentation for multilingual inputs.

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Comparative Evaluation of SVD-TR Model for Eye Gaze-Based Systems

Advances in Intelligent Systems and Computing, 2016

Eye gaze techniques require a number of eye inputs which can be taken by a capturing device like ... more Eye gaze techniques require a number of eye inputs which can be taken by a capturing device like digital camera, webcam, etc. These eye inputs are usually in the form of digital images. With some powerful software, features can be removed or replaced in a digital image without any detectable trace and such operations are called tampering. Tampering also includes the addition of noise which is an unwanted data applied to image to disturb its basic features and results in false information. Therefore, it becomes essential to identify the tampering extent for such images. In this research, SVD-based noise detection and removal (SVD-TR) model has been applied to remove noise (salt-pepper and Gaussian) from eye gaze-based image database. The results show that SVD-TR model removes noise effectively from eye gaze-based image database. To check the efficiency of SVD-TR model, the results obtained are compared with median filter.

Evaluating Interactivity with Respect to Distance and Orientation Variables of GDE Model

Proceedings of the International Congress on Information and Communication Technology, 2016

Eye gaze-based system requires the correct estimation and detection of gaze. Gaze-based input is ... more Eye gaze-based system requires the correct estimation and detection of gaze. Gaze-based input is processed to initiate different commands remotely in computing systems. However, various factors like interactivity, processor affinity, distance, orientations, light, image resolution, etc., affect the detection of gaze in the eye gaze models. In this research paper, work has been done to evaluate the processing time for the estimation of gaze direction for detecting the variations in interactivity for gaze-based models w.r.t. distance and orientation parameters of the subject. The experimental work has been done using gaze detection and estimation (GDE) model. The different results obtained by varying the number of processor affinities for finding the minimum CPU time taken by the model for different eye images. These results can further be used for improving and minimizing the interactivity time for enhancing the accuracy and performance of eye gaze-based systems.

Non-Overlapping Block-based Parametric Forgery Detection Model

by Kusam Sharma and Pawanesh Abrol

International Journal of Computer Applications, Jan 15, 2016

Modification of a digital image by adding or removing some of its elements using a wide variety o... more Modification of a digital image by adding or removing some of its elements using a wide variety of image processing tools results in image forgery. As a result authentication of originality of a digital image is becoming a challenging task. Copy-paste forgery is one of the forgeries belonging to context based forgery. Copy-Paste Forgery Detection (CPFD) aims at finding regions that have been copied and pasted within the same or different image. A small change in the image may change statistical parameters that can be analysed for initial assessment of the forgery. In the present research study, a parametric forgery detection model using nonoverlapping block-based technique is developed to ascertain the copy-paste forgery in a given digital image. Statistical parameters of the input image are computed, analysed and compared with those of the forged image. The results show that the proposed model identifies the forged area of the given image and works well with low to moderate copy-paste forgery. The results obtained can be used as the initial verification of the images for forgery and to enhance the forgery detection process by identifying most likely cases of possible image forgeries. The proposed model is tested with large domain of images having different dimensions and for detecting forgery within an image. However, the model has limitations with certain geometrical transformations.

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Eye Gaze Techniques for Human Computer Interaction: A Research Survey

International Journal of Computer Applications, 2013

Human Computer Interaction (HCI) is an emerging technology. Eye gaze technique is one of the very... more Human Computer Interaction (HCI) is an emerging technology. Eye gaze technique is one of the very significant techniques of HCI and can be used as hands free pointing tool enabling hands-free operation of the display for the user. The important advantage in using eye gaze systems is that the user can communicate from a distance, and there is no requirement of physical contact with the computer. Investigation of eye gaze helps to understand various aspects of the user like attention, intention, desire and area of interest etc. The eye gaze detection techniques can be classified on the basis of direct eye detection, appearance, template, shape, feature, motion, hybrid, regression, 3D methods etc. There are significant factors like shape and size of the object, distance from the subject, texture, light conditions, colour, orientation, head movement, calibration which may influence and affect the efficiency and effectiveness of the eye gaze detection. The use of the gaze as a human computer interface in different fields is an example of high end applications of these techniques. Eye detection is being used in many real time and interactive high end applications. These include the tracking and analyzing of driver"s behaviour with the head pose detection. It is being used for assessing consumer"s shopping behaviour, pointing and selection, activating commands and combinations with other pointing devices, in surgical and medical applications. Moreover eye gaze techniques are also useful for designing and development of various devices especially for differently abled users. In this paper an extensive research survey has been carried out to understand and analyze the study of various eye gaze techniques, algorithms and models. On the basis of survey of various techniques of eye gaze, a general overview of different phases of eye gaze processing has been presented. Certain technical factors have been identified that are significant and relevant for the working of the models. In the literature survey a number of parameters that are significant for estimation, detection, better efficiency and accuracy of eye gaze techniques have been studied and analysed. A comparison and analytical discussion of different eye gaze techniques and models have been presented. The analysis and classification of the models shall be helpful for further improvement and optimization in the performance and accuracy of eye gaze techniques.

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Experimental analysis of digital image retrieval using SVD

2014 International Conference on Computing for Sustainable Global Development (INDIACom), 2014

Two techniques of the most known ones for peak to average power ratio (PAPR) reduction of orthogo... more Two techniques of the most known ones for peak to average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) are selected mapping (SLM) and partial transmit sequence (PTS). Both schemes were proposed as distortion less PAPR reduction algorithms. However, it has been an argument to prove which scheme is the most efficient. In this paper, we propose a new PAPR reduction efficiency parameter which will be applied on the complementary cumulative distribution function (CCDF) of each technique to compare the results. We show as well how the performance of the system reacts when increasing the probability of getting high PAPR values. Using the proposed efficiency formula, we show that PTS system performance improves when increasing the probability, whereas the SLM system performance gets impaired when increasing the probability within the same range.

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Study and Analysis of Software Development and User Satisfaction Level

Communications in Computer and Information Science, 2009

... Deepshikha Jamwal, Pawanesh Abrol, and Devanand Padha Dept. ... Cost (February 2008) ISSN 097... more

Recursion in Java: A Quantative Analysis

Advances in Computational Sciences …, 2010

1 Asst. Professor, E-mail: jamwalsnj@yahoo.com 2 Sr. Asst. Professor, E-mail: pawanesh_a@yahoo.co... more

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