Compact diffraction grating laser wavemeter for cold atom experiments

We present an innovative and practical scheme of building a miniaturized wavemeter, with the advantages of low cost, high reliability and simple structure. Through a calibration test by a 780 nm external cavity diode laser (ECDL), the results show that our system gets a wavelength resolution of better than 1 pm, measurement accuracy of better than 2 pm (corresponding to a frequency of 1 GHz), and a measurement range of 8.5 nm. Finally, the multi-mode comparison test between our system and a commercial spectrum analyzer further indicates the high-precision, miniaturization and low cost of the proposed system, which shows that it is particularly suitable for ECDL and atom cooling and trapping experiments. The system design, experimental results and conclusions are of definite significance as a fine reference for other ranges of wavelength.     

Robust watermarking against print and scan attack through efficient modeling algorithm

This article proposes a blind discrete wavelet transform-discrete cosine transform (DWT-DCT) composite watermarking scheme that is robust against print and scan distortions. First, two-dimensional DWT is applied to the original image to obtain the mid-frequency subbands. Then, a one-dimensional DCT is applied to the selected mid-frequency subbands to extract the final coefficients for embedding the watermark. To specify watermarking parameters, we utilize a Genetic Algorithm to achieve a predefined image quality after watermark insertion. Suitable locations for watermarking are determined by analyzing the effect of a modeling algorithm. This model simulates noise and nonlinear attacks in printers and scanners through noise estimation and system identification methods. The experimental results demonstrate that the proposed algorithm has a high robustness against print and scan attack such that its robustness is higher than related watermarking algorithms.     

An accurate pose measurement method of workpiece based on rapid extraction of local feature points

Ceramic sanitary products with complex curved surfaces are generally fragile and difficult to clamp. If the industrial robot is utilized to realize the automatic grinding of such products, the precise positioning of the product is required firstly. In this paper, an accurate pose measurement system for complex curved surface parts is designed by point cloud registration algorithm. In order to improve the stability of the system, this paper combines the advantages of normal vector features and fast point feature histogram (FPFH) features, and proposes a point cloud registration algorithm based on the rapid extraction of local feature points. Experimental results verify that the improved algorithm has improved both efficiency and accuracy, and the system can effectively achieve accurate positioning of products.     

Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks

A new blind digital image watermarking algorithm with watermark embedded in discrete cosine transform (DCT) coefficients is presented in this paper. The proposed scheme exploits correlation between DCT coefficients in neighborhood blocks for embedding. The watermark is embedded by modifying two DCT coefficients, one pertaining to a block in which watermark bit (0 or 1) is to be embedded and the other corresponding to the selected neighborhood block. Both the selected coefficients are modified by a modification factor so that the difference between the pair of coefficients is brought to a predefined zone. This difference between two DCT coefficients is used to extract watermark. The proposed technique has been tested for different attacks like JPEG compression, rotation, cropping, filtering, gaussian noise, salt and pepper noise, histogram equalization etc. It has been observed that the scheme is highly robust not only for the above mentioned attacks used singularly, but also for different possible combinations of simultaneous attacks. A comparison of the proposed technique with some state of art existing algorithms reveals that our scheme provides better results in terms of quality of watermarked images, payload and robustness.     

Contourlet-based image adaptive watermarking

In the contourlet transform (CT), the Laplacian pyramid (LP) decomposes an image into a low-frequency (LF) subband and a high-frequency (HF) subband. The LF subband is created by filtering the original image with 2-D low-pass filter. However, the HF subband is created by subtracting the synthesized LF subband from the original image but not by 2-D high-pass filtering the original image. In this paper, we propose a contourlet-based image adaptive watermarking (CIAW) scheme, in which the watermark is embedded into the contourlet coefficients of the largest detail subbands of the image. The transform structure of the LP makes the embedded watermark spread out into all subbands likely in which the LF subbands are included when we reconstruct the watermarked image based on the watermarked contourlet coefficients. Since both the LF subbands and the HF subbands contain watermarking components, our watermarking scheme is expected to be robust against both the LF image processing and the HF image processing attacks. The corresponding watermarking detection algorithm is proposed to decide whether the watermark is present or not by exploiting the unique transform structure of LP. With the new proposed concept of spread watermark, the watermark is detected by computing the correlation between the spread watermark and the watermarked image in all contourlet subbands fully. The proposed CIAW scheme is particularly superior to the conventional watermarking schemes when the watermarked image is attacked by some image processing methods, which destroy the HF subbands, thanks to the watermarking components preserved in the LF subbands. Experimental results show the validity of CIAW in terms of both the watermarking invisibility and the watermarking robustness. In addition, the comparison experiments prove the high-efficiency of CIAW again.     

Multi-scale detector optimized for small target

The effectiveness of deep learning networks in detecting small objects is limited, thereby posing challenges in addressing practical object detection tasks. In this research, we propose a small object detection model that operates at multiple scales. The model incorporates a multi-level bidirectional pyramid structure, which integrates deep and shallow networks to simultaneously preserve intricate local details and augment global features. Moreover, a dedicated multi-scale detection head is inte...     

一种基于小波变换与奇异分解的图像水印算法

提出一种基于离散小波变换(Discrete Wavelet Transform,DWT)与奇异值分解(Singular Value Decomposition,SVD)相结合的数字水印算法。该算法将原始图像的小波子图进行奇异值分解,将灰度水印图像进行Arnold变换以及扰乱加密,再进行分块离散余弦变换(Discrete Cosine Transform,DCT),将变换后的系数分类嵌入到相应的奇异值中。实验仿真表明,这种方法能抗大多数图像处理攻击,具有良好的鲁棒性。     

A GAN based method for multiple prohibited items synthesis of X-ray security image

Detecting prohibited item based on convolutional neural networks(CNNs) is of great significance to ensure public safety. However, the natural occurrence of such prohibited items is a small-probability event, collecting enough datasets to support CNN training is a big challenge. In this paper, we propose a new method for synthesizing X-ray security image with multiple prohibited items from semantic label images basing on Generative Adversarial Networks(GANs). Theoretically, we can use it to synthesize as many X-ray images as needed. A new generator architecture with Res 2 Net is presented, which is more effective in learning multi-scale features of different prohibited items images. This method is extended by establishing the semantic label library which contains 14 000 images. So we totally synthesize 14 000 Xray security images. The experimental results show the super performance(Fréchet Inception Distance(FID) score of 30.55). And we achieve 0.825 of mean average precision(m AP) with Single Shot Multi Box Detector(SSD) for object detection, demonstrating the effectiveness of our approach.     

彩色数字水印嵌入技术

本文提出一种将彩色数字水印嵌入到灰度级图像中的方法.利用静态图像的压缩编码技术,将彩色数字水印编码为一系列二值ID数字,以实现水印的嵌入.由于水印的嵌入过程是基于原始图像的离散余弦变换(DCT)系数之间的关系,所以水印的提取不需要原始图像.实验结果表明本文提出的数字水印技术,经某些图像处理操作和有损压缩后仍是鲁棒的.     

一种基于离散余弦变换与奇异值分解的数字图像水印算法

结合奇异值分解（SVD）和离散余弦变换（OCT）的特点,提出了一种基于离散余弦交换与奇异值分解的数字图像水印算法.该算法能够很好地解决透明性和鲁棒性之间的矛盾.算法中采用经过置乱变换的灰度图作为水印,不仅增加了嵌入的信息量,而且提高了水印的安全性.实验结果表明,该算法不仅具有较好的透明性,而且对常见攻击如：叠加噪声、JPEG压缩、滤波以及几何攻击等具有较好的鲁棒性.     

A blind DCT based color watermarking algorithm for embedding multiple watermarks

Multiple watermarking based techniques are receiving more attention in recent times for its wide variety of applications in different fields. To protect the copyright ownership and validate the authenticity of multiple owners, in this paper a color multiple watermarking method based on DCT (Discrete Cosine Transform) and repetition code is proposed and simulated. Initially, green and blue components of color host image are selected for inserting multiple watermarks. Then, each green and blue component of the image is decomposed into non overlapping blocks and subsequently DCT is employed on each block. In this technique, a binary bit of watermark is embedded into green/blue component’s transformed block by modifying some middle significant AC coefficients using repetition code. During multiple watermarks embedding in green and blue components of the proposed method, DC and some higher AC coefficients are kept intact after zigzag scanning of each DCT block to ensure the imperceptibility of the watermarked host image. The proposed scheme is experimented to establish the validity by extracting adequate multiple watermark data from the restructured cover image after applying common geometric transformation attacks (like rotation, cropping, scaling and deletion of lines/columns etc.), common enhancement technique attacks (like lowpass filtering, histogram equalization, sharpening, gamma correction, noise addition etc.) and JPEG compression attacks.     

Secure and robust host-adapted color image watermarking using inter-layered wavelet-packets

This work presents a secure and robust color image watermarking for copyright protection applications, that is based on exploiting the multi-spectral properties of the primary color components of the RGB image. The proposed scheme employs the interconnection between the subbands of the primary color components in the wavelet-packet domain. The scheme is constructed to be adaptive, in the sense that the watermark bits are embedded in safe locations, depending on the inter-layer energy of coefficients in the wavelet-packets. The scheme immunity to attacks is improved by applying a two-level security procedure. To validate the high performance of the proposed scheme, several experimental tests were conducted and a comparative analysis was provided. The obtained results have shown improved watermarking robustness against a wide range of attacks while preserving a high watermarking imperceptibility.     

Performance analysis for geometrical attack on digital image watermarking

We present a technique for irreversible watermarking approach robust to affine transform attacks in camera, biomedical and satellite images stored in the form of monochrome bitmap images. The watermarking approach is based on image normalisation in which both watermark embedding and extraction are carried out with respect to an image normalised to meet a set of predefined moment criteria. The normalisation procedure is invariant to affine transform attacks. The result of watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. Here, direct-sequence code division multiple access approach is used to embed multibit text information in DCT and DWT transform domains. The proposed watermarking schemes are robust against various types of attacks such as Gaussian noise, shearing, scaling, rotation, flipping, affine transform, signal processing and JPEG compression. Performance analysis results are measured using image processing metrics.     

基于DCT变换的彩色图像置乱数字水印算法

介绍了离散余弦变换的系数特征,提出了一种基于离散余弦变换的彩色图像置乱数字水印算法。算法是将数字水印置乱加密后微小的扰动原始彩色图像经离散余弦变换后的对应系数,从而达到数字水印嵌入的目的。仿真实验表明算法简单高效,原图像与嵌入水印后图像差异小,水印提取准确,能较好的保证数字水印不可感知性,在对嵌入水印图像进行各种加噪、裁剪、旋转、锐化等处理后,水印仍有较强的鲁棒性。     

Image restoration of finger-vein networks based on encoder-decoder model

Finger-vein recognition is widely applied on access control system due to the high user acceptance and convince. Improving the integrity of finger-vein is helpful for increasing the finger-vein recognition accuracy. During the process of finger-vein imaging, foreign objects may be attached on fingers, which directly affects the integrity of finger-vein images. In order to effectively extract finger-vein networks, the integrity of venous networks is still not ideal after preprocessing of finger vein images. In this paper, we propose a novel deep learning based image restoration method to improve the integrity of finger-vein networks. First, a region detecting method based on adaptive threshold is presented to locate the incomplete region. Next, an encoder-decoder model is used to restore the venous networks of the finger-vein images. Then we analyze the restoration results using several different methods. Experimental results show that the proposed method is effective to restore the venous networks of the finger-vein images.     

离散小波变换和奇异值分解相融合的彩色图像水印算法

为加强数字多媒体的版权保护,提出了一种结合离散小波变换和奇异值分解相融合的彩色图像水印算法(DWT-SVD).首先对彩色数字载体图像进行小波分解,并对其小波系数进行奇异值分解;然后对水印信息采用Arnold进行置乱,并进行奇异值分解;最后将水印信息的奇异值嵌入到彩色图像的小波系数奇异值中,并对水印嵌入强度进行调节.仿真结果表明,DWT-SVD可以检测到完整的水印信息,具有良好的不可见性,对各种攻击具有较强的鲁棒性.     

一种新的基于复合变换域灰度数字水印算法

文章提出了一种新的结合Arnold置乱变换的复合变换域灰度数字水印嵌入算法。该算法利用系数间的相关性对原始图像离散小波变换后的低频系数LL进行离散余弦变换,然后在其中嵌入水印,在嵌入水印之前对Arnold变换预处理的灰度水印图像作离散余弦变换,这样增强了水印的鲁棒性和不可见性。实验结果证明,该算法能有效抵抗JPEG图像压缩和常见的图像处理操作攻击。     

GAN-based data augmentation of prohibited item X-ray images in security inspection

Convolutional neural networks (CNNs) based methods for automatic discriminant of prohibited items in X-ray images attract attention increasingly. However, it is difficult to train a reliable CNN model using the available X-ray security image databases, since they are not enough in sample quantity and diversity. Recently, generative adversarial network (GAN) has been widely used in image generation and regarded as a power model for data augmentation. In this paper, we propose a data augmentation method for X-ray prohibited item images based on GAN. First, the network structure and loss function of the self-attention generative adversarial network (SAGAN) are improved to generate the realistic X-ray prohibited item images. Then, the images generated by our model are evaluated using GAN-train and GAN-test. Experimental results of GAN-train and GAN-test are 99.91% and 98.82% respectively. It implies that our model can enlarge the X-ray prohibited item image database effectively.     

基于混沌置乱和混沌加密的DCT域数字水印算法

把混沌理论应用到图像置乱中,提出了基于混沌的数字图像置乱算法.利用混沌加密算法来对水印数据进行加密,能有效防止攻击者根据统计学方法来检测到水印.然后,对载体图像进行DCT变换,并在DCT域上嵌入水印.通过抗攻击仿真实验表明,该数字水印算法具有较强的抗剪切攻击和噪声攻击能力.     

基于Baker映射与时空混沌相结合的CT-QR域双彩色鲁棒盲水印算法

针对彩色水印图像的盲提取算法抗几何攻击鲁棒性不强的问题,提出一种Baker映射与时空混沌相结合的轮廓波变换(Contourlet transform,CT)和QR分解双彩色强鲁棒盲水印算法。首先将彩色水印分离成RGB分量,对三个分量分别进行Baker映射与时空混沌相结合的预处理操作,然后对载体图像的RGB分量分别进行Contourlet变换,分块QR分解得到酉矩阵,最后根据嵌入规则将加密后的水印分通道的嵌入到酉矩阵中。水印提取时利用Radon变换对图像进行几何校正可提高其几何攻击的鲁棒性。仿真结果表明,该算法不仅使嵌入水印后的图像具有良好的不可见性,而且能有效抵抗加噪、滤波、JPEG压缩、剪切、平移、旋转、马赛克、篡改等攻击,NC值均在0.9以上,对组合攻击也有较强的鲁棒性。