Papers by Keyword: Radon Transform

Abstract: Nowadays, X-ray tomography is one of the most pertinent directions of the development of non-destructive testing methods. Besides the experimental setup to conduct the X-ray tomographic measurements, it is necessary to have stable and flexible software. In most cases, existing software packages for the reconstruction of tomographic data are not freeware. This makes tomographic experiments not flexible because of the restriction of the source code correction. This papers explains how to implement one of important parts of tomographic research, namely, experimental data simulation, which allows to test reconstruction algorithms further.

Abstract: In this paper, a print-scan resilient image watermarking scheme based on Radon transform and DCT(discrete cosine transform) is proposed. The watermark is preprocessed with a chaotic sequence, then the host image is transformed to frequency domain by block DCT. The preprocessed watermark is adaptively embedded into the transform domain coefficients by modulating the relationship between neighbor coefficients. The watermark detection process is accomplished without referring to the original image. Simulation results show good robustness against several attacks, such Jpeg compression, cropping, filtering and so on.

Abstract: Vibroseis obtained the seismic record by cross-correlation detection calculation. compared with dynamite source, cross-correlation detection can suppress random noise, but produce more correlation noise. This paper studies Radon transform to remove correlation noise produced by electromagnetic drive vibroseis and impact rammer. From the results of processing field seismic records, we can see that Radon transform can remove correlation noise by vibroseis, the SNR of vibroseis seismic data is effectively improved.

Abstract: To solve lane detection problem in the system of autonomous vehicle, this paper proposes a method of texture segment based on perspective transformation. In this paper, firstly road images were captured through cameras installed on the vehicle, then make a perspective transform to road plane, so that the road and the non-road texture information effectively stand out. After calculation of the texture trend in the transformed image, radon transform can effectively distinguish between the road and the non-road area, and achieve the purpose of the texture regional segment. Experiments prove that this method can be used on the lane detection, which eliminate barriers and road borders effectively.

Abstract: This paper is about the object rotational motion estimation based on optical flow equation. Being a non-touch measuring technique, it is of important value in some special occasions. It is to set up rigid motion equations by optical flow character, and then using two-step iterative method to estimate motion equation and calculate rotation speed for each coordinate axis. We present a simplified calculation method for some object which specific structure parameters are known. The experiment results show the calculation is accurate.

Abstract: Introduce a complete system of license plate recognition: using morphological processing and priori knowledge of license plate to discern the location of license plate, accomplishing tilt correction through Radon transform, then fulfilling character segmentation of accurate positioning license plate by projection, finishing character recognition through BP neural network which was improved by the use of adaptive learning rate and momentum factor. With the programming and verification on Matlab experimental platform, experimental results show that we can have a preferable recognition speed and accuracy.

Abstract: Nowadays, Hough transform is always adopted to detect the seam-line of mosaic image. But the calculation is big, so the seam-line detection speed is affected obviously. In order to overcome this problem, a new detection method based on radon transform is proposed in the paper. First, a binary image is generated by edge detection technique, after the mosaic image has been smoothed based on mathematical morphology. Second, Radon transform is used to the binary image, and the extreme coordinates of the Radon transform result are determined. Finally, the seam-line location in mosaic image is determined by using the extreme coordinates. The theoretical analysis and experiment results show that the proposed method has very good detection performance.

Abstract: This paper presents an algorithm for estimating the parameters of polynomial-phase signals (PPSs). This algorithm combines the CPF-HAF method and Radon transform, and can be referred to as the Radon-CPF-HAF method. In the proposed algorithm, the HAF is first applied on the original PPS to produce a cubic phase signal, whose parameters are then estimated by the Radon transform of the cubic phase function for the derived cubic phase signal. As involving in lower order nonlinearity, the proposed algorithm outperforms the HAF in terms of the accuracy and signal-to-noise-ratio (SNR) threshold. When multicomponent PPSs are considered, the product version of the proposed algorithm removes the identifiability problem which the product version of the CPF-HAF (PCPF-HAF) suffers from. Computer simulations have been carried out to support the theoretical results.

Abstract: Mojette Transform (MOT) is used mainly in imaging implementation of mechatronicbased imaging system to reconstruct a discrete signal from a finite set of projection planes. The MOT uses a specific algorithm, called Corner Based Inversion (CBI), to reconstruct an image from its projections offering high-speed computing properties. Moreover, the MOT ensures a very low complexity in comparison to the reconstruction based on Fast Fourier Transform (FFT). In this paper, Graphic Processing Unit (GPU) based MOT is presented and also CPU and GPU processing are issued from 1283 image pixels. In the result, performance differences between the CPU and GPU architectures are discussed, and an approach of fast improvement in architectural efficiency is recommend.

Abstract: Point spread function (PSF) estimation and image restoration algorithm are the hotspots In the research of motion blurred image restoration. In order to improve the efficacy of image restoration, an improved algorithm named quadric transforms (QT) method is proposed in this paper by analyzing the restoration process of motion blurred images. Firstly, Fourier transform and homomorphism transform are applied to the original motion blurred image, and then the Fourier transform and homomorphism transform are used again to the obtained spectrum image. Secondly, the motion blur direction is estimated by Radon transform. Thirdly, the motion blur length is found by differential autocorrelation operations. Finally, utilizing the estimated blur direction and blur length, the motion blurred image is restored by Wiener filtering. Experimental results show that the proposed QT method can get more accurate estimated motion blur angles than the primary transform (PT, that is, Fourier transform and homomorphism transform are used one time) method and can get better restored images under the meaning of peak signal to noise ratio (PSNR).