|Statement||C. R. Christensen, J. Upatnieks andB. D. Guenther|
|Series||Technical report -- T-79-18|
|Contributions||Upatnieks, J., Guenther, B. D.|
|The Physical Object|
|Pagination||1 microfiche (35fr)|
|Number of Pages||35|
Optical identification (ID) tags  have a promising future in a number of applications such as the surveillance of vehicles in transportation, control of restricted areas for homeland security. As an input image, the data content of a TV picture is used which makes the correlator compatible with many standard TV components. It is shown that useful correlations can be obtained with such low-resolution systems and can be used for both vehicle tracking and by: A vehicle tracking and grouping algorithm is presented in this work using sparse optical flow method of Lukas-Kanade Tracking technique. A system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. To improve efficiency, every frame of the sequence is down-sampled. Figure 5: Block tracking with four additional navigational area sensors. 4. TRACKING WITH OPTICAL CORRELATOR The velocity of image motion in the focal plane of the camera defines the attitude update rate. The update time has a low boundary, determined by the time that is required for the block to pass the overall sensor by:
Optical coherent receivers operate on the principle of mixing an incoming optical field (information channel) with a high power local oscillator (LO) signal prior to detection by the photodetector. When the frequencies of the LO and incoming optical field carrier are the same, the baseband signal isFile Size: 1MB. The work deals with automatic vehicle detection and classification based on image features. The real images of vehicles mainly 2 wheeler and 4 wheeler are captured using a digital camera with 10 MP. The image database includes 2 wheeler and 4 wheeler separately. The images are enhanced by Size: KB. Optical Correlator (OC) is device to compare two or more images or two dimensional (2D) data sets in very high speed or in real time [1, 5, 12, 18, 24]. Optical correlation is defined as the product of Fourier Transform of the two original functions, s(x,y) and r(x,y) which . Application Study for an Optical Correlator Executive Summary 4-October Page 3 TECHNISCHE UNIVERSITÄT DRESDEN 3. Identification and selection of the perspective applications Altogether 9 perspective applications for optical correlator technology in space have been identified during the first part of the study. 1.
The simplest optical autocorrelation is that of the ﬁeld autocorrelation where the electric ﬁeld, E, is what we are interested in. The electric ﬁeld is a function of time and so we write its autocorrelation as, A(1)(τ) = Z ∞ −∞. E(t)E∗(t−τ)dt where τ is the delay introduced. We implement a fully automatic fast face recognition system by using a frame/s optical parallel correlator designed and assembled by us. The operational speed for the 1:N (i.e., matching one image against N, where N refers to the number of images in the database) identification experiment ( face images) amounts to less than s, including the preprocessing and postprocessing by: Vehicle tracking is one of the popular topics in computer vision field. It is also considered as one of the challenges in computer vision field, as motion tracking can be quite tricky. Unlike human, computer does not possess self-learning ability, thus also make them unable to track . Tracking Accuracy Using Optical Tracking as Standard Depth (mm) AP Distance (mm) Lateral Distance (mm) Axial Distance (mm) All depths ± ± ± Pre-Clinical Prostate Phantom Tests •Using Optical Guidance known shifts are introduced using a translation table. •Optical Guided System is blinded to introduced shiftsFile Size: 2MB.