Karthik R

Pratibha Balaji, Shruthi Narayan, Durga Sraddha et al.

This paper gives a broader insight on the application of adaptive filter in noise cancellation during various processes where signal is transmitted. Adaptive filtering techniques like RLS, LMS and normalized LMS are used to filter the input signal using the concept of negative feedback to predict its nature and remove it effectively from the input. In this paper a comparative study between the effectiveness of RLS, LMS and normalized LMS is done based on parameters like SNR (Signal to Noise ratio), MSE (Mean squared error) and cross correlation. Implementation and analysis of the filters are done by taking different step sizes on different orders of the filters.

Manas Jain, Shruthi Narayan, Pratibha Balaji et al.

In this project, we aim to classify the speech taken as one of the four emotions namely, sadness, anger, fear and happiness. The samples that have been taken to complete this project are taken from Linguistic Data Consortium (LDC) and UGA database. The important characteristics determined from the samples are energy, pitch, MFCC coefficients, LPCC coefficients and speaker rate. The classifier used to classify these emotional states is Support Vector Machine (SVM) and this is done using two classification strategies: One against All (OAA) and Gender Dependent Classification. Furthermore, a comparative analysis has been conducted between the two and LPCC and MFCC algorithms as well.

Anirudh Itagi, Ritam Sil, Saurav Mohapatra et al.

Misclassification of medicine is perilous to the health of a patient, more so if the said patient is visually impaired or simply did not recognize the color, shape or type of medicine strip. This paper proposes a method for identification of medicine strips by 2-D cepstral analysis of their images followed by performing classification that has been done using the K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Logistic Regression (LR) Classifiers. The 2-D cepstral features extracted are extremely distinct to a medicine strip and consequently make identifying them exceptionally accurate. This paper also proposes the Color Gradient and Pill shape Feature (CGPF) extraction procedure and discusses the Binary Robust Invariant Scalable Keypoints (BRISK) algorithm as well. The mentioned algorithms were implemented and their identification results have been compared.

Karthik R, Anvita Dwivedi, Haripriya M et al.

Image inpainting algorithms are used to restore some damaged or missing information region of an image based on the surrounding information. The method proposed in this paper applies the radial based analysis of image inpainting on GRNN. The damaged areas are first isolated from rest of the areas and then arranged by their size and then inpainted using GRNN. The training of the neural network is done using different radii to achieve a better outcome. A comparative analysis is done for different regression-based algorithms. The overall results are compared with the results achieved by the other algorithms as LS-SVM with reference to the PSNR value.

Chetan Sai Tutika, Charan Vallapaneni, Karthik R et al.

In this paper, we develop a method to detect vacant parking spaces in an environment with unclear segments and contours with the help of MATLAB image processing capabilities. Due to the anomalies present in the parking spaces, such as uneven illumination, distorted slot lines and overlapping of cars. The present-day conventional algorithms have difficulties processing the image for accurate results. The algorithm proposed uses a combination of image pre-processing and false contour detection techniques to improve the detection efficiency. The proposed method also eliminates the need to employ individual sensors to detect a car, instead uses real-time static images to consider a group of slots together, instead of the usual single slot method. This greatly decreases the expenses required to design an efficient parking system. We compare the performance of our algorithm to that of other techniques. These comparisons show that the proposed algorithm can detect the vacancies in the parking spots while ignoring the false data and other distortions.

Karthik R, Raghavendra Karthik, Pramod S et al.

Web Application finger printing is a quintessential part of the Information Gathering phase of (ethical) hacking. It allows narrowing down the specifics instead of looking for all clues. Also an application that has been correctly recognized can help in quickly analyzing known weaknesses and then moving ahead with remaining aspects. This step is also essential to allow a pen tester to customize its payload or exploitation techniques based on the identification so to increase the chances of successful intrusion. This paper presents a new tool "W3-Scrape" for the relatively nascent field of Web Application finger printing that helps automate web application fingerprinting when performed in the current scenarios.