Architecture in Water
This paper deals with the understanding of what is architecture in water. The main aim is to understand its types, study its evolution, its scope in the current scenario, a brief study of construction techniques, sustainable approaches, problems faced while and after construction. At last, the aim is to arrive at a conclusion that why architecture in water is important.
Published by: Manali Surana
Author: Manali Surana
Paper ID: V3I2-1577
Paper Status: published
Published: April 26, 2017
Performance Evaluation of a Modified Method Based On Patch Based Image Modelling For Image Denoising
Digital images play a significant role both in daily life as well as in areas of research and technology. Data sets collected by image sensors are generally infected by noise. Imperfect instruments, problems with the data acquisition process, and interfering natural phenomena can all degrade the data of interest. Furthermore, noise can be introduced by transmission errors and compression. Thus, denoising process is often a necessary and the first step to being taken before the images data is being analyzed. It is necessary to apply an efficient denoising technique to compensate for such data corruption. Image denoising still remains a challenge for researchers because noise removal introduces artifacts and causes blurring of the images. The challenge of any image denoising algorithm is to suppress noise while producing sharp images without loss of finer details. A modified method based on patch-based image modeling is proposed in this research work. The main part of proposed method is the use of image nonlocal self-similarity (NSS) prior. NSS prior refers to the fact that a local patch often has many nonlocal similar patches to it across the image. This fact significantly enhances the denoising performance. Patch Groups are extracted from training images by putting nonlocal similar patches into groups. According to these Patch Groups, Gaussian Mixture Model learning algorithm is developed to learn the NSS prior. The whole process is repeated 4 times to make the system learn more and more. The iteration process regulates and optimized some of the variables. MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio) and Correlation coefficient has been taken as output parameters to evaluate the performance of proposed system. MATLAB R2013a has been taken as implementation platform using image processing toolbox.
Published by: Renu Sharma, Gaurav Kumar Sangal
Author: Renu Sharma
Paper ID: V3I2-1575
Paper Status: published
Published: April 26, 2017
Survey of Various Methods for Image Denoising
An Image is a worth, a thousand words & in this digital age, images are everywhere. Most of the digital images contain some form of noise. The purpose of denoising is to reconstruct the original image from its noisy observation as accurately as possible. The important property of a good image denoising model is that it should completely remove noise as far as possible. Estimation of the noise level in an image is a very important parameter to improve the efficiency of denoising. This article presents different approaches used so far by the researchers for the estimation of blind noise level using the statistical and averaging method and denoising of an image. The paper also contains problems in different approaches identified by the survey. Image denoising has a very rich history beginning from the mid-70s. Patch based image modeling has achieved a great success in low-level vision such as image denoising. In particular, the use of image nonlocal self-similarity (NSS) prior, which refers to the fact that a local patch often has many nonlocal similar patches to it across the image, has significantly enhanced the denoising performance. However, in most existing methods only the NSS of input degraded image is exploited, while how to utilize the NSS of clean natural images is still an open problem.
Published by: Renu Sharma, Gaurav Kumar Sangal
Author: Renu Sharma
Paper ID: V3I2-1574
Paper Status: published
Published: April 26, 2017
Identification of Human Actions in Video Database
The Human activity detection is a more highly sought research as they are used for the Surveillance, Health care system, content based search, and interactive game applications. The Human activity recognition is carried out by three main stages namely object segmentation, feature extraction, their representation and human action detection using different algorithms. This paper is an attempt to identify the human activities such as running, jogging, clapping and hand waving in a video database using the method of bag of features which is the extension of bag of words. The Size Invariant Feature Transform (SIFT) based bag of SIFTs is used for the local feature extraction from the images that are chosen for the human activity detection. After finding the SIFT features for both the database and the query video, the query video features are compared with each of the database video features, the distance is found using Euclidean Distance method and the K Nearest Neighbor classifier is used to find the classified category from the list of the video . Matlab based implementation is done with various activities identified and their efficiencies are compared.
Published by: Smita S. Patil, Santosh Saraf
Author: Smita S. Patil
Paper ID: V3I2-1572
Paper Status: published
Published: April 26, 2017
Use of Global Portal for giving Preferences while Online Food Ordering
Food zone is basically a website which focuses on online food ordering. The system is convenient for the customers. It sets up menu online and the customers can easily place order. This application can also be used by developing cities where it is difficult for the restaurants to publish themselves. One can register for its restaurant, cake shop, bakery products, Mess and a lot more. Once registered, then can receive order and provide services. If any order is not available then it is redirected to global portal where it is accessed by other subscribers. Quick access functionality for user creates an attachment with restaurants. Also, there is a module for the customer to book a table. Even customer can give feedback to any restaurant so further filtering process is done.
Published by: Minal M. Surve, Manali Mahadeo Thakur, Sharvari Rajendra Khanore, Mangesh K. Gosavi
Author: Minal M. Surve
Paper ID: V3I2-1564
Paper Status: published
Published: April 26, 2017
Review of Industrial Waste used in Stabilization of Expansive Soil in Road Subgrade
The Aim of this review paper is to study the various industrial waste used for stabilization of Expansive soil in road subgrade. Expansive soil have tremendous strength but it becomes very soft when it getting wet, It expands/swell due to its mineralogical composition during its wet condition, It creates cracks or consolidated when it is dry. Expansive soils can be found on almost all the continents on the Earth. First various literature was studied and finally an industrial waste Iron Sludge was suggested because of its higher density for stabilization of expansive soil.
Published by: Ahemadabbas S. Rajpura, Prof. B. R Shah, Prof. H. K Dave
Author: Ahemadabbas S. Rajpura
Paper ID: V3I2-1560
Paper Status: published
Published: April 26, 2017
