Pixel Matching Algorithm Research Articles

Extracting high-precision full-field displacement from videos via pixel matching and optical flow

Accurate sensing of full-field displacements plays a significant role in dynamic testing for structural health monitoring (SHM). Recently, video camera has become a more promising tool in displacement sensing due to advantages such as low price, agility, simultaneous measurement, and high spatial sensing resolution. Traditional target tracking approaches (e.g., digital image correlation, template matching, etc.) typically require clear targets on the structure surface and thus only provide sparse displacement. Phase-based motion extraction enables full-field displacement measurement at subpixel precision without the need of markers as tracking targets, which has achieved great success in structural modal identification among many other SHM applications. However, the phase-based approach in a Eulerian framework fails to deal with large motions. To tackle these challenges, an enhanced phase-based method, that synergistically combines the developed local amplitude supplemented pixel matching algorithm and optical flow processing, is proposed for full-field displacement sensing with subpixel precision meanwhile capable of dealing with large motions. In particular, the pixel matching estimates the integer-pixel motion vectors of pixels which have sufficient texture contrast determined by local amplitude. The optical flow, represented by the first order Taylor series, is then employed to approximate the rest subpixel motion associated with the integer-pixel motion vectors. The proposed technique is validated by processing a field-test videos with LVDT reference and then applied to other several lab/field recorded videos of different vibrational objects for displacement extraction and modal identification.

Laser stripe matching algorithm with coplanar constraint in underwater laser scanning systems

In order to obtain the precise three-dimensional (3-D) points of underwater objects, we propose a corresponding pixel matching algorithm based on coplanar constraint for underwater laser scanning systems. It uses three coplanar constraints of left camera, right camera, and laser plane to achieve high-precision and high-speed pixel matching according to the characteristics of underwater laser scanning system. Results show that the measurement error is

Binocular high dynamic range imaging system based on digital micromirror device

In the applications of scientific imaging and space exploration, the dynamic range of imaging systems is usually required to reach more than 120 dB. In order to observe a highly dynamic scene in real time, we designed an imaging system based on a digital micromirror device (DMD) that is used as a spatial light modulator. First, we designed a binocular highly dynamic light-adjusting system based on a DMD according to the DMD’s optical structure. Second, in order to realize the registration between the micromirrors of a DMD and pixels of the two cameras, a pixel-matching algorithm was developed. Finally, we introduce a novel light-adjusting algorithm that can recover the highly dynamic data of the dynamic scene. Experiments showed that the deviation between the DMD and the two cameras is reduced to 0.48 pixels after correction, and that bright and dark targets in a high-dynamic-range scene can both be displayed simultaneously in one image with high quality after light adjustment. The dynamic range of the system is theoretically 209 dB, which meets the requirements of high-dynamic-range observation.

A Novel Architecture for Information Security using Division and Pixel Matching Techniques

The computer users have to safeguard the information which they are handling. An information hiding algorithm has to make sure that such information is undecipherable since it may have some sensitive information. This paper proposes a steganography method that conceals the message behind the image by providing the security when compared to the other existing methods. In this system, the information to be hidden is encrypted by an advanced cryptography technique. For that, initially, the data is divided by the method of arithmetic division. The information is hold on within the style of the divisor, the quotient & the remainder. The secret key is also encrypted and holds on several pixels. Then, the pixel matching algorithm is used to hide the information of the secret image in the carrier image. By this system, the embedding time is reduced when compared to different existing algorithms. In this method, different types of images are used for testing the proposed algorithm. By using this method, the peak signal to noise magnitude relation obtained is more for all the pixels present in the image.

Automated Skin Detection using Fuzzy Logic based Pixel Matching Algorithm

Objectives: Skin detection is the initial process of any automatic face recognition system. One of the fore most common approaches to detect the faces in facial pictures can be done by an automatic face detection method. In this paper, a new type of facial skin detection using the combination of Fuzzy and Pixel matching algorithms is proposed. Method/Statistical Analysis: The proposed system has three steps. Initially, the input facial color image is transformed in to a grey scale image and then, it is sharpened using a filter. Secondly, the pixels of the different types of facial grey scale images are computed. Finally, the computed pixels are compared with the original grey scale image based on the fuzzy rules. This process is done for the first pixel to the last pixel so that all the pixels which are present in the entire image can be included in the overall process. Findings: The algorithm is tested for different types of facial images for both the accuracy and the time taken to complete the skin detection process. The results of the experiments reveal that an accurate skin detection rate of 94.42% for the combination of fuzzy based pixel matching along with the dimension reduction methodology. Application/ Improvements: Future enhancements in this work are to propose an efficient algorithm to detect the facial images of group of faces present in a single image. Keywords: Dimension Reduction, Facial Image, Fuzzy Logic, Pixel Matching Algorithm, Skin Texture Analysis, Skin Detection

航天TDI CCD相机成像拼接快速配准算法设计与分析

In order to solve the problem of multi pieces of TDI CCD stitching pixel mismatch in satellite flexible transformation multimodal imaging, a kind of pixel matching algorithm which can realize overlapping and displacement pixel fast assembly and registration of TDI CCD camera is proposed. Through the analysis of multi pieces of TDI CCD assembly imaging pixel mismatch phenomenon caused by the variation of image motion velocity vector in focal plane during the process of satellite side swing imaging, the imaging velocity vector ray tracing and the homogeneous coordinate transformation method is designed. Based on this method, the image motion velocity and drift angle which influence image mismatch during the process of satellite side swing imaging and the number of pixel in direction of longitudinal displacement and transverse overlapping of two pieces of TDI CCD assembly imaging are calculated. Three-axis air flotation turntable attitude simulation system and a TDI CCD camera are used in experiment to verify the pixel matching algorithm of two pieces of TDI CCD assembly imaging. TDI CCD camera of viewing angle of 10, after an assembly period, the original number of longitudinal displacement and transverse overlapping pixels of two pieces of TDI CCD assembly imaging turns from 148.5 and 50 to 137 and 49, respectively, which is consistent with theoretical result in longitudinal displacement direction and has a deviation of only 0.1 pixel in transverse overlapping direction. Compared with the theoretical and experimental result, the design of fast registration algorithm of calculation of longitudinal displacement and transverse overlapping pixel can solve the accuracy of TDI CCD assembly imaging, which guarantees image pixel matching and obtain high quality images.

Three dimensional tracking of particles and their local orientations

In this paper, digital stereoscopic imaging and reconstruction techniques have been developed for the tracking and velocity measurement of solid particles using a single camera. The variable shutter speeds of a digital camera are used to control the trajectory length of the tracked particles. A colour coding method has been developed to resolve the ambiguity of particle flow direction and avoid the confusion in manually matching particle pairs. The method could be applied to validate the automated particle matching algorithms. Besides using points (particle centroids) a matching algorithm for a stereo reconstruction pixel to pixel matching algorithm has been applied. The latter is able to resolve not only the particle position but also the shape and orientation of a non-spherical particle. This is of importance since non-spherical particle or bubble geometry is common in a practical system and the non-spherical geometry has a strong effect on the particle or bubble dynamics. The potential of using this system for the quantitative 3D measurement of multiphase flow has been demonstrated with several test cases.

Generalized predictive binary shape coding using polygon approximation

Abstract This paper introduces a new binary shape coding technique called generalized predictive shape coding (GPSC) to encode the boundary of a visual object compactly by using a vertex-based approach. GPSC consists of a contour pixel matching algorithm and a motion-compliant contour coding algorithm. The contour pixel matching algorithm utilizes the knowledge of previously decoded contours by using a uniform translational model for silhouette motion, and generalizes polygon approximation for lossless and lossy motion estimation by adjusting a tolerance parameter d max . To represent motion-compliant regions with minimum information in the transmitted bitstream, we develop a reference index-based coding scheme to represent the 2D positions of the matched segments using 1D reference contour indices. Finally, we encode the mismatched segments by sending residual polygons until the distortion is less than d max . While GPSC realizes polygon approximation exactly at every encoding stage, we can guarantee quality of service because the peak distortion is no greater than d max , and we improve coding efficiency as long as a silhouette complies with the model. The tolerance parameter d max can be assigned to each contour to smooth the transmitted data rate, which is especially useful for constant bandwidth channels. Compared with non-predictive approaches, simulation using MPEG-4 sequences demonstrates that GPSC not only improves objective gain but also enhances visual quality based on MPEG-4 subjective tests. The significance of GPSC is that it provides a generic framework for seamlessly extending conventional vertex coding schemes into the temporal domain yet it retains the advantages of existing polygon-based algorithms for visual content description while furnishing better geometric compression.