Effective Method of Image Retrieval Using Markov Random Field with Hough Transform

The emergence of multimedia technology and the rapidly expanding image collections on the database have attracted significant research efforts in providing tools for effective retrieval and management of visual data. The need to find a desired image from a large collection. Image retrieval is the field of study concerned with searching and retrieving digital image from a collection of database .In real images, regions are often homogenous; neighboring pixels usually have similar properties (shape, color, texture) Markov Random Field (MRF) is a probabilistic model which captures such contextual constraints. Hough Transform method is used for detecting lines in binary images. Spatially extended patterns are transformed to produce compact features in a parameter space. The main advantages of using the HT is, it treats each edge point independently this means that the parallel processing of all points is possible which is suitable for real-time applications

Segmentation of Football Video Broadcast

In this paper a novel segmentation system for football player detection in broadcasted video is presented. Proposed detection system is a complex solution incorporating a dominant color based segmentation technique of a football playfield, a 3D playfield modeling algorithm based on Hough transform and a dedicated algorithm for player tracking, player detection system based on the combination of Histogram of Oriented Gradients (HOG) descriptors with Principal Component Analysis (PCA) and linear Support Vector Machine (SVM) classification. For the shot classification the several classification technique SVM, artificial neural network and Linear Discriminant Analysis (LDA) are used. Evaluation of the system is carried out using HD (1280×720) resolution test material. Additionally, performance of the proposed system is tested with different lighting conditions (including non-uniform pith lightning and multiple player shadows) and various camera positions. Experimental results presented in this paper show that combination of these techniques seems to be a promising solution for locating and segmenting objects in a broadcasted video

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

A gridding hough transform for detecting the straight lines in sports video

10.1109/ICME.2005.1521474IEEE International Conference on Multimedia and Expo, ICME 20052005518-52

Ultrasound and motion capture analysis for pre-operative planning in lower limb joint replacement surgeries

Pre-operative planning in total knee and hip arthroplasty is important for surgical outcome and patient satisfaction. Current clinical gold standards for pre-operative planning include imaging methods which are invasive to the patient and limited to one position of analysis. Lower limb and pelvic alignment are assessed in planning for total knee and hip arthroplasty respectively and have shown to vary in their measurements between standing and supine. B-mode ultrasound has shown to be a promising method for gaining superficial structures like muscles and bones. B-mode ultrasound can be performed rapidly and is relatively cheap and measurements can be conducted with the patient in various positions. The aim of this thesis is to establish non-invasive protocols for pre-operative planning in knee and hip surgeries. Several approaches were developed to non-invasively measure lower limb and pelvic alignment. These consisted of using integrated motion capture and ultrasound system (OrthoPilot, Aesculap). A smart system (Aesculap) which consisted of a smart phone, smart tablet and ultrasound device was used to measure pelvic tilt from the anterior pelvic plane. A motion capture system on its own was used to measure the pelvic tilt in alternative manners. And finally, a synchronised ultrasound and motion capture setup was used for three-dimensional reconstructions of bone geometries. Supine and standing measurements were conducted which showed the flexibility of the measurements unlike common alternatives (X-Ray, MRI, CT). Several operators performed precise measurements of key lower limb parameters. For example, varus-valgus was shown to be measured within 1 degree across operators. Femur and tibia segment lengths were also consistent (<5mm maximum variation between operators). Femur and tibia torsion measurements were less reliable (up to 10-15 degrees of variation between operators). Pelvic tilt measurements were also found to be unreliable regardless of the measurement technique. Initial promise and feasibility of three-dimensional reconstructions of all lower limb joint axis for implementation into musculoskeletal models was also shown. Joint contact forces differences between the implementation of MRI and ultrasound parameters into the models were less than 1 body weight. Overall, ultrasound has shown to be useful in the assessment of lower limb parameters and bone geometries. This work has built upon previous findings to continue its development in the field of pre-operative planning and musculoskeletal modelling. Further work will include a large validation of subject-specific musculoskeletal modelling from ultrasound reconstructions. Improvements to the lower limb assessment with OrthoPilot will also be investigated

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Beyond Quantity: Research with Subsymbolic AI

How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately