Optics ,
Opto-electronics ,
digital and analog electronic circuit design ,
Antenna, RF and Microwave circuit design ,
digital image and signal processing ,
pattern recognition
Profile Summary
Looking for an intellectually stimulating job position in the field of electrical engineering
Publications (7)
This will count as one of your downloads.
You will have access to both the presentation and article (if available).
The fringe-adjusted joint transform correlator (JTC) technique has been found to yield substantially better correlation performance than alternate JTC techniques. Since the fringe-adjusted JTC (FJTC) is sensitive to scale and rotation variations, a synthetic discriminant function (SDF) based FJTC was proposed to realize scale and rotation invariant pattern recognition system via computer simulation. In this paper, optoelectronic implementation of the scale and rotation invariant pattern recognition using SDF based FJTC has been tested for both binary and gray level images. The experimental results obtained are in close agreement with the simulation results obtained earlier.
We propose a novel decision fusion algorithm for target tracking in forward-looking infrared (FLIR) image sequences recorded from an airborne platform. The algorithm allows the fusion of complementary ego-motion compensation and tracking algorithms to estimate the position of the target in the current frame among a sequence of frames of FLIR imagery. We identified three modes that contribute to the failure of the tracking system: (1) the sensor ego-motion failure mode, which causes the movement of the target beyond the operational limits of the tracking stage; (2) the tracking failure mode, which occurs when the tracking algorithm fails to determine the correct location of the target in the new frame; (3) the reference-image distortion failure mode, which happens when the reference image accumulates walkoff error, especially when the target is changing in size, shape, or orientation from frame to frame. The strategy in our design is to prevent these failure modes from producing tracking failures. The overall performance of the algorithm is guaranteed to be much better than any individual tracking algorithm used in the fusion. One important aspect of the proposed algorithm is its recoverability: the ability to recover following a failure at a certain frame. The experiments performed on Army Missile Command AMCOM FLIR data set verify the robustness of the algorithm.
To achieve scale and rotation invariant pattern recognition, we implemented synthetic discriminant function (SDF) based reference image in a nonzero order Fringe-adjusted Joint Transform Correlator (FJTC) using binary random phase mask. The binary random phase mask encodes the SDF based reference image before it is introduced in the joint input image. The joint power spectrum is then multiplied by the phase mask to remove the zero-order term and false alarms that may be generated in the correlation plane due to the presence of multiple identical target or non-target objects in the input scene. Detailed analysis for the proposed SDF based nonzero order FJTC using binary random phase mask is presented. Simulation results verify the effectiveness of the proposed technique.
A near real-time invariant multi-target tracking algorithm based on the fringe-adjusted joint transform correlator (FJTC) technique is proposed for forward looking infra-red (FLIR) image sequences. The proposed FJTC based tracking approach uses a modified synthetic discriminant function (SDF) concept together with an efficient camera motion compensation technique to accommodate the problem of target signature variation due to 3D distortions and noise. The proposed technique can track small objects comprising of only a few pixels and is capable of compensating the high ego-motion of the sensor. The robustness of the proposed technique is demonstrated with computer simulation performed on sequences of real life FLIR imagery taken from an airborne moving platform.
A novel real-time-invariant target tracking algorithm is proposed for forward-looking IR (FLIR) image sequences based on a modified synthetic discriminant function (SDF)-based fringe-adjusted joint transform correlator (JTC) algorithm. The proposed approach utilizes fringe-adjusted JTC-based tracking, which efficiently compensates camera motion and accommodates 3-D distortions. To further increase the tracking accuracy, the target model is continuously updated using a modified version of the synthetic discriminant function (SDF) algorithm. The proposed technique can track small objects comprising only a few pixels and is capable of compensating the high egomotion of the sensor. We demonstrate the robustness of the proposed technique by computer simulation performed on sequences of real-life FLIR imagery taken from an airborne moving platform.
Presented in this paper is a fringe-adjusted joint transform correlator (FJTC) based invariant target tracking of forwar looking infra-red (FLIR) image sequences. The proposed FJTC based tracking approach employed a modified synthetic discriminant function (SDF) concept together with an efficient camera motion compensation technique to accommodate the problem of target signature variation due to in-plane/out-of-plane rotations, scale variations, noise, and bad frames. The proposed technique can track small objects comprising of only a few pixels and is capable of compensating the high ego-motion of the sensor. The robustness of the proposed technique is demonstrated with computer simulation performed on sequences of eal life FLIR imagery taken from an airborne moving platform.
In this paper, we propose a novel decision fusion algorithm for target tracking in forward looking infrared (FLIR) image sequences recorded from an airborne platform. The algorithm allows the fusion of complementary ego-motion compensation and tracking algorithms. We identified three modes that contribute to the failure of the tracking system: (1) the sensor ego-motion failure mode, which causes the movement of the target more than the operational limits of the tracking stage; (2) the tracking failure mode, which occurs when the tracking algorithm fails to determine the correct location of the target in the new frame; (3) the distortion of the reference image failure mode, which happens when the reference image accumulates walk-off error, specially when the target is changing in size, shape or orientation from frame to frame. The proposed algorithm prevents these failure modes from developing unrecoverable tracking failures. The overall performance of the algorithm is guaranteed to be much better than any individual tracking algorithm used in the fusion. The experiments performed on the AMCOM FLIR data set verify the robustness of the algorithm.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.