Pixel Matching Research Articles

Performance of a hybrid photon detector prototype with electrostatic cross-focussing and integrated silicon pixel readout for Cherenkov ring detection

We report on the first test beam performance of a hybrid photon detector prototype, using binary readout electronics, intended for use in the ring imaging Cherenkov detectors of the LHCb experiment at the CERN Large Hadron Collider. The photon detector is based on a cross-focussed image intensifier tube geometry. The anode consists of a silicon pixel array bump-bonded to a binary readout chip with matching pixel electronics. The detector has been installed in a quarter-scale prototype vessel of the LHCb ring imaging Cherenkov system. Focussed ring images produced by 120 GeV/c negative pions traversing an air radiator have been recorded. The observed light yield and Cherenkov angle resolution are discussed.

Dense disparity estimation with a divide-and-conquer disparity space image technique

A new divide-and-conquer technique for disparity estimation is proposed in this paper. This technique performs feature matching following the high confidence first principle, starting with the strongest feature point in the stereo pair of scanlines. Once the first matching pair is established, the ordering constraint in disparity estimation allows the original intra-scanline matching problem to be divided into two smaller subproblems. Each subproblem can then be solved recursively until there is no reliable feature point within the subintervals. This technique is very efficient for dense disparity map estimation for stereo images with rich features. For general scenes, this technique can be paired up with the disparity-space image (DSI) technique to compute dense disparity maps with integrated occlusion detection. In this approach, the divide-and-conquer part of the algorithm handles the matching of stronger features and the DSI-based technique handles the matching of pixels in between feature points and the detection of occlusions. An extension to the standard disparity-space technique is also presented to compliment the divide-and-conquer algorithm. Experiments demonstrate the effectiveness of the proposed divide-and-conquer DSI algorithm.

Low-complexity overlapped block motion estimationusingpattern-based pixel matching

A novel motion estimation method is presented which significantly reduces the computational complexity of overlapped block motion estimation (OBME). To eliminate the computationally intensive multiplications of OBME, the proposed method uses a predetermined pattern in selecting matched pixels within a window support. Simulation results show that the proposed method achieves about the same prediction performance as the conventional approach.

Object oriented face detection usingcolour transformation and range segmentation

A range segmentation technique using a matching pixel count (MPC) disparity histogram is combined with the generalised facial colour distribution (GFCD) skin-colour transform technique to provide robust multiple facial object detection with depth-range selectivity in a complex background environment.

The study of the radiance variation between two pixels for their stereo vision matching

In the stereo vision system, the key problem is a search problem which finds the corresponding pixels in the two stereoscopic images. These pixels must satisfy a very strict photometric constraint. In our approach, we use a special configuration of the two cameras in order to speed up the stereo vision process. In this paper, a theoretical study of the radiance variation between two stereo vision matching pixels is presented. This study shows the efficiency and the limitation of the used photometric constraint. Furthermore, we show the influence of the maximum value of the disparity and the one of the focal length of the two cameras on the stereo vision process. Some experimental results obtained on real images are given in the end of this paper.

A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification

A detailed comparison of the backpropagation neural network and maximum-likelihood classifiers for urban land use classification is presented. Landsat Thematic Mapper images of Tucson, Arizona, and Oakland, California, were used for this comparison. For the Tucson image, the percentage of matching pixels in the two classification maps was only 64.5%, while for the Oakland image it was 83.3%. Although the test site accuracies of the two Tucson maps were similar, the map produced by the neural network was visually more accurate; this difference is explained by examining class regions and density plots in the decision space and the continuous likelihood values produced by both classifiers. For the Oakland scene, the two maps were visually and numerically similar, although the neural network was superior in suppression of mixed pixel classification errors. From this analysis, the authors conclude that the neural network is more robust to training site heterogeneity and the use of class labels for land use that are mixtures of land cover spectral signatures. The differences between the two algorithms may be viewed, in part, as the differences between nonparametric (neural network) and parametric (maximum-likelihood) classifiers. Computationally, the backpropagation neural network is at a serious disadvantage to maximum-likelihood, taking nearly an order of magnitude more computing time when implemented on a serial workstation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A Portable Dual Energy X-ray Absorptiometry Technique for the Measurement of Bone Mineral in Preterm Infants

A dual energy x-ray absorptiometry technique has been developed for the measurement of bone mineral in preterm infants. Two films are taken of the infant's forearm using a standard mobile x-ray set on the ward at two x-ray energies. Included in the field of view is a double step wedge made of aluminum and Perspex. The images are digitized by viewing them on a light box with a TV camera. The bone mineral content in the forearm can then be mapped by the measurement of light intensity in matching pixels of the two films and comparison with the intensities in the step wedge. The bone mineral concentration in the radius, expressed as bone mineral per unit length (mg/mm), is calculated. The technique has been tested using phantoms of calcium hydroxylapatite set in a tissue equivalent material and in Perspex. It has been shown that the reproducibility of the technique is approximately 7% and that there is a systematic underestimate of bone mineral of about 17%. The technique has been shown to be linear up to a bone mineral concentration of 8 mg.mm-1. Longitudinal studies for 14 infants that show an initial 6-wk period of demineralization after birth with a subsequent mineralization phase are reported.

A 1006 element hybrid silicon pixel detector with strobed binary output

An asynchronous version of a binary pixel readabout circuit has been implemented in an array with 16 columns at 500 mu m pitch and 63 rows at 75 mu m pitch. This readabout chip has been bonded with solder bumps to a silicon detector with matching pixel elements. Event information in a pixel can be strobed into a local memory by a trigger signal and subsequently read out. Without a strobe the information is continuously cleared. The complete hybrid detector has been successfully tested with ionizing particles from a radioactive source. Three such devices have been put in the CERN heavy-ion experiment WA94 in the Omega spectrometer, where they recorded particle tracks from high-multiplicity /sup 32/S interactions. Preliminary data indicate a noise of approximately 60 e/sup -/ and a threshold spread of approximately 500 e/sup -/. The timing characteristics are adequate for a fixed-target experiment. >