Syed Irtiza Ali Shah

A novel approach to CAD system for the detection of lung nodules in CT images

Detection of pulmonary nodule plays a significant role in the diagnosis of lung cancer in early stage that improves the chances of survival of an individual. In this paper, a computer aided nodule detection method is proposed for the segmentation and detection of challenging nodules like juxtavascular and juxtapleural nodules. Lungs are segmented from computed tomography (CT) images using intensity thresholding; brief analysis of CT image histogram is done to select a suitable threshold value for better segmentation results. Simple morphological closing is used to include juxtapleural nodules in segmented lung regions. K-means clustering is applied for the initial detection and segmentation of potential nodules; shape specific morphological opening is implemented to refine segmentation outcomes. These segmented potential nodules are then divided into six groups on the basis of their thickness and percentage connectivity with lung walls. Grouping not only helped in improving systems efficiency but also reduced computational time, otherwise consumed in calculating and analyzing unnecessary features for all nodules. Different sets of 2D and 3D features are extracted from nodules in each group to eliminate false positives. Small size nodules are differentiated from false positives (FPs) on the basis of their salient features; sensitivity of the system for small nodules is 83.33%. SVM classifier is used for the classification of large nodules, for which the sensitivity of the proposed system is 93.8% applying 10-fold cross-validation. Receiver Operating Characteristic (ROC) curve is used for the analysis of CAD system. Overall sensitivity of the system is 91.65% with 3.19 FPs per case, and accuracy is 96.22%. The system took 3.8 seconds to analyze each image.

3D Obstacle Detection Using a Single Camera

This paper aims at detecting obstacles using a single camera in an unknown three dimensional world, for 3D motion of an unmanned air vehicle. Obstacle detection is a pre-requisite for collision-free motion of a UAV through 3D space. Most research towards vision based obstacle detection and avoidance has been done for 2D planar motion of ground robots and using active sensors like laser range finders, sonar, radar etc. Passive camera based research has mostly been done, either using stereo vision (multiple cameras) or, by developing a prior expectation map of the world and its comparison with the new image data. In this paper, an attempt has been made to find a 3D solution of the obstacle detection problem using a single camera in an unknown world. The equations developed and the simulations results presented here, show that a 3D model of the scene can be generated from 2D image information from a single camera flying through a very small arc of lateral flight around the object, without the need of capturing images from all sides as in a typical ‘structures from motion’ problem. The forward flight simulation results show that the depth extracted from forward motion is in fact usable for large part of the image, which is a significant contribution of this work.

Motion Estimation for Obstacle Detection and Avoidance Using a Single Camera for UAVs/Robots

This work focuses on efficient and effective vision systems for object detection for ground & aerial robots venturing into unknown environments, with minimum possible vision aids onboard, i.e. a single camera. The existing approaches to solve such a problem include ‘Structures From Motion’, Optical Flows and ‘Flow Field Divergence’, etc. These approaches have been analyzed here for various constraints involved, and the Motion Estimation technique has been proposed to solve for obstacle detection problem for collision avoidance, using a single camera. This technique not only overcomes various constraints of other approaches, but also retains most of their merits. Its implementation on synthetically generated images as well as on some real videos from a UAV, has been proved successful to solve this problem. However, while implementing the technique on UAVs in actual flight, quite a few undesirable motion vectors have been encountered. An analysis of such implementation issues has been presented next, along with proposed solutions. After adequately addressing such issues, the application of this approach is being attempted on any of Georgia Tech’s aerial robotic platforms.

Development of an autonomous flight controller for surveillance UAV

This paper presents the different stages of development of flight controller for unmanned aerial vehicle (UAV) with autonomously flying capability. The main purpose of flight controller is to perform a petrol function between given GPS coordinates while maintaining a specified altitude for an assigned time and then return to its launching position without any human interaction. At first a simulated environment was designed to verify the concept. Then this was implemented on actual unmanned helicopter. In wake of the current political and security situation the need for autonomous UAVs and particularly the small scale helicopters are under consideration. However, hobby airframes used for normal radio controlled flying are not readily compatible with delicate, sophisticated and complex electronics. In addition to the hardware integration with such airframes, several other challenges such as electromagnetic interference, communication signal integrity from jammers and damping of strong vibrations were handled. The goal is to develop an autonomous UAV with self-controlled flying capabilities and above mentioned functionality. It should also fulfil the requirements to perform an adequate surveillance during any political and security situation.

Interaction of robot with humans by communicating simulated emotional states through expressive movements

This paper presents a non-verbal and non-facial method for effective communication of a “mechanoid robot” by conveying the emotions through gestures. This research focuses on human–robot interaction using a mechanoid robot that does not possess any anthropomorphic facial features for conveying gestures. Another feature of this research is the use of human-like smooth motion of this mechanoid robot in contrast to the traditional trapezoidal velocity profile for its communication. For conveying gestures, the connection between motion of robot and perceived emotions is established by varying the velocity and acceleration of the mechanoid structure. The selected motion parameters are changed systematically to observe the variation in perceived emotions. The perceived emotions have been further investigated using three different emotional behavior models: Russell’s circumplex model of affect, Tellegen–Watson–Clark model and PAD model. Results obtained show that the designated motion parameters are linked with the change of emotions. Moreover, the emotions perceived by the user are same through all three models, validating the reliability of all the three emotional scale models and also of the emotions perceived by the user.

A real-time simple light detection application for a flying robot in extreme noise and interference

In this work, a real-time vision-based algorithm has been developed and implemented on a flying robot, in order to detect and identify a light beacon in the presence of excessive colored noise and interference. Starting from very basic and simple image analysis techniques including color histograms, filtering techniques, and color space analyses, typical pixel-based characteristics or a model of the light beacon has been progressively established. It has been found that not only are various color space-based characteristics significant, but also the relationships between various channels across different color spaces are of great consequence, in a beacon detection problem, specifically referring to a blue light-emitting diode. A block-based search algorithm comprising of multiple thresholds and linear confidence level calculation has been implemented to search established model characteristics in real-time video image data. During implementation, once excessive noise was encountered during flight tests, a simple and low cost noise and interference filter was developed. This filter very effectively handled all noise encountered in real time. The proposed work was successfully implemented and utilized on GeorgiaTech’s participating aircraft for the International Aerial Robotics Competition by Association for Unmanned Vehicle Systems International for detection of a blue light-emitting diode problem. Major contributions of this work include establishing a multiple threshold search and detection algorithm based on not only various color channels but also their relationships and handling of as much as 40% noisy or interfered video data with successful practical implementation and demonstration of proposed approach.

Single sensor-based 3D feature point location for a small flying robot application using one camera

Finding the location of feature points in 3D space from 2D vision data in structured environments has been done successfully for years and has been applied effectively on industrial robots. Miniature flying robots flying in unknown environments have stringent weight, space, and security constraints. For such vehicles, it has been attempted here to reduce the number of vision sensors to a single camera. At first, feature points are detected in the image using Harris corner detector, the measurements of which are then statistically corresponded across various images, using knowledge of vehicle’s pose from onboard inertial measurement unit. First approach attempted is that of ego-motion perpendicular to camera axis and acceptable results for 3D feature point locations have been achieved. Next, except for a small region around the focus of expansion, forward translations along the camera axis have also been attempted with acceptable results, which is an improvement to the previous relevant work. The 3D location map of feature points thus obtained is utilizable for trajectory planning while ensuring collision avoidance through 3D space. Reduction of vision sensors to a single camera while utilizing minimum ego-motion space for 3D feature point location is a significant contribution of this work.

Estimation of velocity and pressure profiles to design an optimum Von Karman Viscous Pump

In this work velocity and pressure profiles have been calculated for a generic Von Karman Viscous flow pump using a computer code. Moreover the variation of angular velocities and radii of a flat disc and their effects on velocity and pressure profile have been analyzed. Velocity and pressure plots have been generated for different combinations of radii and angular velocities of the disc in order to design an optimum performance viscous pump using Navier stokes equations in polar coordinates. The effect of viscosity on volume flow rate has also been analysed. Thickness of viscous region and its variation with respect to viscosity of the fluid and angular velocity of the disk have also been analysed. The algorithm developed during the research will facilitate scientific researchers to perform calculations to design an optimum pump. The results achieved will help in designing any generic pump working on Von Karman Viscous Pump principle. Such types of pumps find their application in chemical industries as these pumps are very reliable for highly viscous and abrasive fluids. These pumps are also very steady and exceptionally quiet, finding their usage in air moving applications in interior spaces occupied by humans. In the field of medical these types of pumps have gained attention as lots of research is going on for the treatment of single ventricle heart disease where a single viscous impeller pump, working on the principle of Von Karman Viscous Pump, is used for stabilization and supplements cavopulmonary flow.

Servo actuated payload carry and drop mechanism for unmanned helicopter

Unmanned Aerial Vehicles (UAVs) are more often used now a days for the civilian purposes such as surveillance, surveying, monitoring, and transportation. Unmanned helicopter systems has been used more often for the disaster surveying and monitoring. In order to provide the facility of carrying and dropping the payload from the helicopter, this paper presents a servo actuated payload drop mechanism design for the unmanned disaster relief helicopter. The proposed payload drop mechanism is operated with two servo motors and uses metallic gears based mechanism to carry and drop the payload of up to 9kg. SolidWorks Virtual Computer Aided Design (CAD) platform has been used for the modelling and drop test simulations of proposed mechanism. The proposed mechanism has been designed specifically for the CopterWorks helicopter platform and can be utilized in civilian operations for the carrying and dropping the payload of up to 9kg.

Modeling and analysis of velocity profile of a rectangular aircraft exhaust nozzle

This research is aimed to investigate the flow behavior at the exit plane of a rectangular aircraft exhaust nozzle for different aspect ratios. An algorithm has been developed to evaluate the velocity profile at the exit cross section of a rectangular aircraft exhaust nozzle. The same algorithm has also been used to calculate the velocity field and plot the velocity contours for that cross section. This algorithm has been run for four different aspect ratios. Each aspect ratio has been investigated for three flow regimes i.e. subsonic, supersonic and hypersonic. After running the algorithm for all twelve cases, the results have been compared for finding the optimal aspect ratio for a specific flow regime which offers the maximum flexibility for design of exhaust nozzle. Criteria for the optimal aspect ratio has been based on the maximum exhaust velocity as maximum exit speeds are of prime importance in an engine exhaust nozzle design for thrust maximization. This study would serve as a benchmark for aircraft exhaust nozzle designers and scientists for the future investigation of the impact of varying aspect ratio on exit velocities for rectangular exhaust nozzles. In future, the same analysis may be validated experimentally using the wind tunnel as well as computationally. The proposed methodology may be followed to study other non-circular exhaust nozzles such as elliptic, triangular, rounded rectangle etc. This will give an insight into the behavior of flow when geometric characteristics of the exhaust nozzle are varied. Further it will help to optimize the design of exhaust nozzles as advanced manufacturing technologies have enabled us to manufacture difficult contours without compromising the strength of components.