Automatic extraction of 1D barcodes from video scans for drone-assisted inventory management in warehousing applications

The widespread use of barcodes has significantly contributed to accurate, efficient and economic inventory management in warehouses and distribution centres. However, its efficiency has always been limited by the primary method of reading barcodes with a handheld laser scanner. Compared with this reading by line-of-sight at close proximity, vision-based barcode reading algorithms can further improve efficiency, particularly if accompanied by automated data collection platforms such as drones. This paper introduces algorithms that are able to automatically extract barcodes from video data, and verifies their feasibility and promise for inventory management in warehousing applications. Three key techniques corresponding to different recognition levels are proposed: For a known barcode region, a Harris corner detector and Hough transform-based algorithm is applied to quickly estimate the angle by which the frame area needs to rotate to orient the bars vertically for information extraction. Then, the idea of exploiting connectivity and geometry property of barcode areas is proposed to directly recognise multiple barcode regions in a single video frame to eliminate reading difficulties resulting from interactive influence of multiple juxtaposed barcodes, and to save computation time by only processing frame areas of interest for valid barcodes. In addition, a histogram difference-based fast extraction strategy is designed to further improve efficiency by reducing duplicate information processing. Finally, the performance of each technique is evaluated by analysing video data from a large logistics warehouse, demonstrating satisfactory performance in inventory management applications.     

CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

Does higher government debt link to higher social expenditure? New method,new evidence

Scholars believe that higher social expenditures are usually linked with higher government debts, whereas higher debts reduce social expenditures. However, it is reasonable to speculate that higher government debt may contribute to higher social spending, while fiscal deficits occur during a recession, which commonly creates greater demand for social expenditure. For a deeper investigation, this paper revisits the dynamic relationship between social spending and public debts in the time-frequency domain, using the novel wavelet-coherency analysis as well as the phase-difference technique to derive the co-moved and causal relationships between social spending and public debts in 13 OECD countries. The evidence identifies a dynamic relationship between variables. While higher social expenditures increase government debts, the shocks from government debts to social expenditures are conversely uncertain. We discover that higher government debt does reduce social expenditures, but it may be linked to higher social spending. The robustness of partial coherency and phase-difference discovers the role of a political party in the decision over social welfare programmes in the sample countries.     

一种改进的CPFSK信号频率估计方法

针对突发信号解调中多普勒频偏大的问题，提出了一种改进的连续相位移频键控信号(CPFSK)频率估计方法。首先接收信号平方运算使信号的调制指数加倍，再通过一次离散傅里叶变换(DFT)，用搜索信号平方谱谱峰的方法实现突发信号频率估计。仿真实验表明，在低信噪比条件下，该算法的频率估计精度比经典的相位差频率估计算法提高了20%；该算法与广泛用于高动态突发信号的频率插值估计算法相比，同道干扰信道下信干比改善可达4 dB，DFT长度缩短约1/3。     

Time-frequency co-movements between oil prices and interest rates: Evidence from a wavelet-based approach

This paper investigates time–frequency co-movements between crude oil prices and interest rates. To test this relationship, the study applied a continuous wavelet and cross wavelet approaches to data from West Texas Intermediate (WTI) crude oil prices and interest rates in the United States (U.S.). Results from the sample period revealed significant relationships, in the intermediate term, between WTI crude oil prices and U.S. interest rates. Moreover, co-movements between oil price and interest rate variables were especially sensitive during abnormal political events and periods of financial ‘meltdown’. We further use Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) methods to investigate the impacts of five major control variables namely GDP growth, unemployment, three-month Treasury bill, CPI index and industrial production index. The results show a powerful impact of control variables on oil-interest rates co-movements under different frequencies. Finally, we show evidence of co-integrating long run relationship between oil markets and control variables. These results have important implications for energy investors and policy makers.     

STOCK‐BOND CO‐MOVEMENTS AND FLIGHT‐TO‐QUALITY IN G7 COUNTRIES: A TIME‐FREQUENCY ANALYSIS

This paper examines co‐movement between stock returns and changes in 10‐year government bond yields as well as flight‐to‐quality behaviour in G7 countries. We conduct the wavelet squared coherence analysis to explore the dynamics in both time and frequency domain. Our results provide evidence of positive co‐movements, which vary over time and across investment horizon. The higher co‐movement is found to be more concentrated in the lower frequency bands. We further analyse the dynamic nature of the scale‐dependent wavelet correlations and find that the correlations are highly volatile and significantly increase across different time scales during the episodes of equity market turbulence. The increase in correlations reflects flights from stocks to safer bond investments as a result of dramatic changes in investor sentiment and risk aversion at times of market stress.     

基于小波变换的图像处理综述

小波分析主要广泛应用在科学研究和工程技术中。虽然在现阶段的小波理论相对成熟,近些年关于小波理论的应用和研究也在不断的发展和更新。小波变化在图像处理领域中的应用也囊括图像与处理的所有方面。本文通过介绍小波变换的起源,将小波应用在图像处理中的压缩、还原图像、边缘检测和图像分割,宏观剖析小波的研究现状历史、发展动向及优势。     

Valuation of forward start options under affine jump-diffusion models

Under the general affine jump-diffusion framework of Duffie et al. [Econometrica, 2000, 68, 1343–1376], this paper proposes an alternative pricing methodology for European-style forward start options that does not require any parallel optimization routine to ensure square integrability. Therefore, the proposed methodology is shown to possess a better accuracy–efficiency trade-off than the usual and more general approach initiated by Hong [Forward Smile and Derivative Pricing. Working paper, UBS, 2004] that is based on the knowledge of the forward characteristic function. Explicit pricing solutions are also offered under the nested jump-diffusion setting proposed by Bakshi et al. [J. Finance, 1997, 52, 2003–2049], which accommodates stochastic volatility and stochastic interest rates, and different integration schemes are numerically tested.     

小波域抑制多音干扰的扩频接收机

利用小波包理论提出了一种快速、准确地识别并且抑制多音干扰的有效方法。该方法利用小波包理论将多音干扰的各条谱线逐个定位，然后通过功率谱分析的方法来识别多音干扰的存在区间，最后将被干扰污染的区间逐个切除并反向重构接收到的信号。实验证明该方法的误比特率性能在强干扰时要优于以前的FFT域切割法。     

汽车倾斜牌照中字符的定位与提取

提出了汽车图像中倾斜汽车牌照字符的定位与提取算法。该算法针对汽车牌照的灰度特点,先确定牌照的位置,并从背景中分割出来。对二值化车牌定位图通过Hough变换,计算出车牌主要直线的倾斜角度,通过插值旋转后,重新确定车牌字符的边界,最后精确地提取出汽车牌照中的字符。与其它传统的方法比较,该方法在运算速度和精确性上有一定优势。