Title: Skeleton Matching with Applications in Severe Weather Detection Authors: Mohammad Mahdi Kamani, Farshid Farhat, Stephen Wistar and James Z. Wang. Elsevier Journal: Applied Soft Computing, ~27 pages, May 2017. Abstract: Severe weather conditions cause an enormous amount of damages around the globe. Bow echo patterns in radar images are associated with a number of […]
Abstract: Severe weather conditions cause enormous amount of damages around the globe. Bow echo patterns in radar images are associated with a number of these destructive thunderstorm conditions such as damaging winds, hail and tornadoes. They are detected manually by meteorologists. In this paper, we propose an automatic framework to detect these patterns with high […]
Abstract: Linear perspective is widely used in landscape photography to create the impression of depth on a 2D photo. Automated understanding of the use of linear perspective in landscape photography has a number of real-world applications, including aesthetics assessment, image retrieval, and on-site feedback for photo composition. We address this problem by detecting vanishing points […]
Abstract: Steganalysis of least significant bit (LSB) embedded images in spatial domain has been investigated extensively over the past decade and most well-known LSB steganography methods have been shown to be detectable. However, according to the latest findings in the area, two major issues of very low-rate (VLR) embedding and content-adaptive steganography have remained hard […]
Abstract LSB embedding in spatial domain with very low rate can be easily performed and its detection in spite of many researches is very hard, while BOSS competition has been held to break an adaptive embedding algorithm with low rate. Thus, proposing powerful steganalyzer of very low rate in spatial domain is highly requested. In […]
Abstract: We propose a novel image steganalysis method, based on singular value decomposition and noise estimation, for the spatial domain LSB embedding families. We first define a content independence parameter, DS, that is calculated for each LSB embedding rate. Next, we estimate the DS curve and use noise estimation to improve the curve approximation accuracy. […]
Discovering Triangles in Portraits for Supporting Photographic Creation, S He, Z Zhou, F Farhat, JZ Wang, IEEE Transactions on Multimedia, Aug 2017. Intelligent Portrait Composition Assistance — Integrating Deep-learned Models and Photography Idea Retrieval, F Farhat, MM Kamani, S Mishra, JZ Wang, July 2017. Skeleton Matching with Applications in Severe Weather Detection, MM Kamani, F […]
NEWS SOURCEs [www.sciencedaily.com/releases/2017/06/170621145133.htm www.eurekalert.org/pub_releases/2017-06/ps-nir062117.php phys.org/news/2017-06-leverages-big-severe-weather.html sciencenewsline.com/news/2017062217300053.html] Every year, severe weather endangers millions of people and causes billions of dollars in damage worldwide. But new research from Penn State’s College of Information Sciences and Technology (IST) and AccuWeather has found a way to better predict some of these threats by harnessing the power of big data. […]
Farshid Farhat @ EECS PSU PhD Candidate School of Electrical Engineering and Computer Science The Pennsylvania State University Address: 310 IST Building, University Park, PA, 16802. Email: fuf111 AT psu DOT edu Web: Farshid Farhat ‘s Site About Me I am a member of Intelligent Information Systems (IIS) research lab at Penn State. I am working with Prof. […]
Abstract: Linear perspective is widely used in landscape photography to create the impression of depth on a 2D photo. Automated understanding of linear perspective in landscape photography has several real-world applications, including aesthetics assessment, image retrieval, and on-site feedback for photo composition, yet adequate automated understanding has been elusive. We address this problem by detecting […]