Puneet Goyal

Clustered-Dot Halftoning With Direct Binary Search

In this paper, we present a new algorithm for aperiodic clustered-dot halftoning based on direct binary search (DBS). The DBS optimization framework has been modified for designing clustered-dot texture, by using filters with different sizes in the initialization and update steps of the algorithm. Following an intuitive explanation of how the clustered-dot texture results from this modified framework, we derive a closed-form cost metric which, when minimized, equivalently generates stochastic clustered-dot texture. An analysis of the cost metric and its influence on the texture quality is presented, which is followed by a modification to the cost metric to reduce computational cost and to make it more suitable for screen design.

Learner's perspective on video-viewing features offered by MOOC providers: Coursera and edX

Although the foundation for Massive Open Online Courses (MOOCs) was laid down around 2008, it is in the recent years that there has been observed the stupendous rise of MOOCs. Currently there has been much debate regarding its pros and cons. While access to high speed internet connection, computer systems and possessing a decent knowledge of the language that the course is instructed in (usually English) may prove to be barriers in some countries, this digital education offering has undoubtedly provided a learning edge to students and others, who can overcome these hurdles, irrespective of their geographical location, financial condition and time constraints. The two MOOC providers: Coursera and edX, have emerged as the major MOOC services over the years due to their tie-ups with numerous prestigious universities, free courses, user-friendly interface, and strong business model. The learning is primarily through videos and the MOOCs learners spend significant time in viewing course videos. This paper is the first survey-based study of its kind, to the best of our knowledge, conducted to explore the learners perspective on video-viewing features offered by these two MOOC providers The survey assesses video-viewing related features on Coursera and edX namely, subtitle captions/transcripts, in-video quizzes, video duration, quality and video speed varying feature as experienced by the student participants, who have participated in both edX-offered courses and Coursera-offered courses.

Cost function analysis for stochastic clustered-dot halftoning based on direct binary search

Most electrophotographic printers use periodic, clustered-dot screening for rendering smooth and stable prints. However, periodic, clustered-dot screening suffers from the problem of periodic moir´e resulting from interference between the component periodic screens superposed for color printing. There has been proposed an approach, called CLU-DBS for stochastic, clustered-dot halftoning and screen design based on direct binary search. This method deviates from conventional DBS in its use of different filters in different phases of the algorithm. In this paper, we derive a closed-form expression for the cost metric which is minimized in CLU-DBS. The closed-form expression provides us with a clearer insight on the relationship between input parameters and processes, and the output texture, thus enabling us generate better quality texture. One of the limitations of the CLU-DBS algorithm proposed earlier is the inversion in the distribution of clusters and voids in the final halftone with respect to the initial halftone. In this paper, we also present a technique for avoiding the inversion by negating the sign of one of the error terms in the newly derived cost metric, which is responsible for clustering. This not only simplifies the CLU-DBS screen design process, but also significantly reduces the number of iterations required for optimization.

Electro-photographic model based stochastic clustered-dot halftoning with direct binary search

Most electrophotographic printers use periodic, clustered-dot screening for rendering smooth and stable prints. However, when used for color printing, this approach suffers from the problem of periodic moire´ resulting from interference between the periodic halftones of individual color planes. There has been proposed an approach, called CLU-DBS for stochastic, clustered-dot halftoning and screen design based on direct binary search. We propose a methodology to embed a printer model within this halftoning algorithm to account for dot-gain and dot-loss effects. Without accounting for these effects, the printed image will not have the appearance predicted by the halftoning algorithm. We incorporate a measurement-based stochastic model for dot interactions of an electro-photographic printer within the iterative CLU-DBS binary halftoning algorithm. The stochastic model developed is based on microscopic absorptance and variance measurements. The experimental results show that electrophotography-model based stochastic clustered dot halftoning improves the homogeneity and reduces the graini-ness of printed halftone images.

Electro-photographic-model-based halftoning

Most halftoning algorithms assume there is no interaction between neighboring dots or if there is, it is additive. Without accounting for dot-gain effect, the printed image will not have the appearance predicted by the halftoning algorithm. Thus, there is need to embed a printer model in the halftoning algorithm which can predict such deviations and develop a halftone accordingly. The direct binary search (DBS) algorithm employs a search heuristic to minimize the mean squared perceptually filtered error between the halftone and continuous-tone original images. We incorporate a measurementbased stochastic model for dot interactions of an electro-photographic printer within the iterative DBS binary halftoning algorithm. The stochastic model developed is based on microscopic absorptance and variance measurements. We present an efficient strategy to estimate the impact of 5×5 neighborhood pixels on the central pixel absorptance. By including the impact of 5×5 neighborhood pixels, the average relative error between the predicted tone and tone observed is reduced from around 21% to 4%. Also, the experimental results show that electrophotography-model based halftoning reduces the mottle and banding artifacts.

Efficiently improving the security of OTP

The easy, convenient and remote access to internet is definitely changing the way we live. It has also become a major factor in the financial lives of millions. Using the Internet to carry out online banking simplifies our financial affairs when compared to the traditional banking method. The inclusion of Online Banking by different sectors like health, financial, educational institutions etc. which accounts for most of the population has not only increased its importance but at the same time has attracted the cyber criminals to take the advantage of the loopholes in the process of online transaction. The cybercriminals can make use of these loopholes and carry out transaction which might not come in the knowledge of user and the bank. Recent studies have shown that the OTP which was developed as a part of two factor authentication is vulnerable to attacks. In this paper, we present a new framework for enhancing authentication during online transaction which secures our OTP.

Sub-block Features Based Image Retrieval

In various domains like security, education, biomedicine etc., the volume of digital data is increasing rapidly, and this is becoming a challenge to retrieve the information from the storage media. Content-based image retrieval systems (CBIR) aim at retrieving from large image databases the images similar to the given query image based on the similarity between image features. This paper aim to discuss and solve the problem of designing sub-block features based image retrieval. Firstly, this paper outlines a description of the primitive features of an image. Then, the proposed methodology for partitioning the image and extracting its colour and texture is described. The algorithms used to calculate the similarity between extracted features, are then explained. Finally, we compared with some other existing CBIR methods, using the WANG database, which is widely used for CBIR performance evaluation, and the results demonstrate the proposed approach outperforms other existing methods considered.

Efficiently denoising SMS text for FAQ retrieval

Several online resources in the form of Frequently Asked Questions (FAQs) provide useful and much needed information across different domains like health, education, banking etc. Community based service has emerged as a powerful resource for information retrieval but its access is restricted to internet only.To access information without internet facility more and more people rely on Short Message Service (SMS) to get an instant answer to their query.Therefore, efforts have been put to improve the SMS based information retrieval system. The text in SMS messages are generally noisy and correcting this noisy text is one of the major challenges that affect the efficiency and accuracy of any SMS based information retrieval system. This paper provides the improvements to the existing algorithms of noise removal in SMS text to obtain better results. Experiments using different test cases show that the proposed system outperforms other methods.

Stochastic clustered-dot screen design for improved smoothness

Printers employing electrophotographic technology typically use clustered-dot screening to avoid potential artifacts caused by unstable dot rendering. Periodic clustered-dot screens are quite smooth, but also suffer from periodic moir´e artifacts due to interference with other color channels. Stochastic, clustered-dot screens provide an alternative solution. In this paper, we introduce a new approach for stochastic, clustered-dot screen design based on Direct Binary Search (DBS). The method differs from the conventional DBS in its use of a modified cost metric which was derived in an earlier work from using different filters in the initialization and update phases of DBS. The objective of the chosen approach is to design screen for improved print smoothness by generating a homogeneous distribution of compact, uniformly-sized clusters. The results include halftone of a screened folded-ramp, compared against a screen designed with a previous method.

Print quality assessment for stochastic clustered-dot halftones using compactness measures

Most electro-photographic printers prefer clustered-dot halftone textures for rendering smooth and stable prints. Clustered-dot halftone patterns can be periodic or aperiodic. As periodic clustered-dot halftone can lead to undesirable moiré patterns, stochastic clustered-dot halftone textures are more preferred. There are available different screening methods to generate stochastic clustered-dot halftone textures but there are no standard print quality assessment measures that can be easily used for quantitatively evaluating and comparing different stochastic clustered-dot halftoning methods. We explore the use of compactness measures for this purpose, and also propose a new compactness measure that seems good metric to quantitatively compare and assess the print quality of different stochastic clustered-dot halftoning methods. Using the proposed metric, we compare three different stochastic clustered-dot halftoning methods, and our results are almost in agreement with psychophysical experiments results reported earlier.