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Detection of violence and weaponized violence in closed-circuit television (CCTV) footage requires a comprehensive approach. In this work, we introduce the \emph{Smart-City CCTV Violence Detection (SCVD)} dataset, specifically designed to facilitate the learning of weapon distribution in surveillance videos. To tackle the complexities of analyzing 3D surveillance video for violence recognition tasks, we propose a novel technique called \emph{SSIVD-Net} (\textbf{S}alient-\textbf{S}uper-\textbf{I}mage for \textbf{V}iolence \textbf{D}etection). Our method reduces 3D video data complexity, dimensionality, and information loss while improving inference, performance, and explainability through salient-super-Image representations. Considering the scalability and sustainability requirements of futuristic smart cities, the authors introduce the \emph{Salient-Classifier}, a novel architecture combining a kernelized approach with a residual learning strategy. We evaluate variations of SSIVD-Net and Salient Classifier on our SCVD dataset and benchmark against state-of-the-art (SOTA) models commonly employed in violence detection. Our approach exhibits significant improvements in detecting both weaponized and non-weaponized violence instances. By advancing the SOTA in violence detection, our work offers a practical and scalable solution suitable for real-world applications. The proposed methodology not only addresses the challenges of violence detection in CCTV footage but also contributes to the understanding of weapon distribution in smart surveillance. Ultimately, our research findings should enable smarter and more secure cities, as well as enhance public safety measures., Comment: Contains 5 tables and 3 figures. Accepted at the 2024 SAI Computing Conference

We present the study of stellar populations in the central 5.5 arcmin (~1.2 kpc) of the M31 bulge by using the optical colour magnitude diagram derived from the observations taken by HST Advanced Camera for Surveys observations. In order to enhance image quality and then obtain deeper photometry, we construct Nyquist-sampled images and use a deconvolution method to detect sources and measure their photometry. We demonstrate that our method performs better than DOLPHOT in the extremely crowded region. The resolved stars in the M31 bulge have been divided into nine annuli and the colour magnitude diagram fitting is performed for each of them. We confirm that the majority of stars (> 70 per cent) in the M31 bulge are indeed very old (> 5 Gyr) and metal rich ([Fe/H] ~ 0.3). At later times, the star formation rate decreased and then experienced a significant rise around 1 Gyr ago, which pervaded the entire M31 bulge. After that, stars formed at less than 500 Myr ago in the central 130 arcsec. Through simulation, we find that these intermediate-age stars cannot be the artefacts introduced by the blending effect. Our results suggest that although the majority of theM31 bulge are very old, the secular evolutionary process still continuously builds up the M31 bulge slowly. We compare our star formation history with an older analysis derived from the spectral energy distribution fitting, which suggests that the latter one is still a reasonable tool for the study of stellar populations in remote galaxies. © 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society.

For the past decades, the decoration of packaging plays an important role in promoting the product to the consumer, especially related to the fast moving consumer products. As the product decoration field had attracted much attention, there is a demand to strengthen its effect of decoration to packaging industry. Therefore, one of the active research studies in packaging decoration is to improve the clarity and special effect on the decoration image using image processing techniques. Currently, there has tremendous number of drawing package or computer-aided design software for aiding design in general, but none of them specifically built for packaging decoration purpose. The aim of this thesis is to develop an application for packaging decoration purpose that allow user to apply image processing algorithm onto the decoration image and subsequently paste the decoration image on a flat and curve surface in order the decoration image to be viewed at different angles. In order to validate the efficiency of the developed application to achieve the stated aims, two experiments are conducted on the collected 1000 decoration images. The analysis results concludes the developed application is successfully allow user to improve the quality of the appearance clarity of the decoration image by applying selected image processing algorithm and subsequently further verified the effect of the pasted decoration image on the surfaces of the packaging

For the past decades, the decoration of packaging plays an important role in promoting the product to the consumer, especially related to the fast moving consumer products. As the product decoration field had attracted much attention, there is a demand to strengthen its effect of decoration to packaging industry. Therefore, one of the active research studies in packaging decoration is to improve the clarity and special effect on the decoration image using image processing techniques. Currently, there has tremendous number of drawing package or computer-aided design software for aiding design in general, but none of them specifically built for packaging decoration purpose. The aim of this thesis is to develop an application for packaging decoration purpose that allow user to apply image processing algorithm onto the decoration image and subsequently paste the decoration image on a flat and curve surface in order the decoration image to be viewed at different angles. In order to validate the efficiency of the developed application to achieve the stated aims, two experiments are conducted on the collected 1000 decoration images. The analysis results concludes the developed application is successfully allow user to improve the quality of the appearance clarity of the decoration image by applying selected image processing algorithm and subsequently further verified the effect of the pasted decoration image on the surfaces of the packaging