Detecting splicing and copy-move attacks in color images

Image sensors are generating limitless digital images every day. Image forgery like splicing and copy-move are very common type of attacks that are easy to execute using sophisticated photo editing tools. As a result, digital forensics has attracted much attention to identify such tampering on digital images. In this paper, a passive (blind) image tampering identification method based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) has been proposed. First, the chroma components of an image is divided into fixed sized non-overlapping blocks and 2D block DCT is applied to identify the changes due to forgery in local frequency distribution of the image. Then a texture descriptor, LBP is applied on the magnitude component of the 2D-DCT array to enhance the artifacts introduced by the tampering operation. The resulting LBP image is again divided into non-overlapping blocks. Finally, summations of corresponding inter-cell values of all the LBP blocks are computed and arranged as a feature vector. These features are fed into a Support Vector Machine (SVM) with Radial Basis Function (RBF) as kernel to distinguish forged images from authentic ones. The proposed method has been experimented extensively on three publicly available well-known image splicing and copy-move detection benchmark datasets of color images. Results demonstrate the superiority of the proposed method over recently proposed state-of-the-art approaches in terms of well accepted performance metrics such as accuracy, area under ROC curve and others.2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 201

Detection of Malleefowl Mounds from Point Cloud Data

Airborne light detection and ranging (LiDAR) data have become cost and time-efficient means for estimating the size of timid fauna populations through the identification of artefacts that evidence their occurrence in a large, hostile geographic area. The unobtrusive detection method helps conservation managers to assess the stability of a population and to design appropriate conservation programs. Here we propose a mound (nest) detection method for Australia's native iconic bird, the Malleefowl, from point cloud data, which can be manipulated to act as a surrogate for population data. Existing detection methods are largely through manual observations, and are therefore not efficient for covering large and remote areas. The proposed mound detection method can identify mound feature based on height and intensity values provided by the point cloud data. Each candidate mound point is initially selected by applying a height threshold utilising the classified ground points and their corresponding digital elevation model (DEM). Then, another threshold based on intensity range derived from ground truth mound area analysis is applied on the extracted initial mound points to find the final candidate mound points. These extracted points are then used to generate a binary mask where the potential mound points are found sparse. To connect those points, a morphological filter is applied on the binary image and found the mound separated from other remaining non-mound objects. To obtain the mound from other non-mound objects, a morphological cleaning operation and a connected component analysis are carried out on the mask. The non-mound objects are removed from the mask utilising the area property of mound derived from the empirical analysis of ground-truth observations. Finally, the effectiveness of the proposed technique is calculated based on ground truth. Although the mound shapes and structures are highly variable in nature, our height and intensity-based mound point extraction method detected 55 % of the ground-truthed mounds. © 2021 IEEE

Antioxidant, analgesic and anti-inflammatory activities of the methanolic extract of Piper betle leaves

Objective:The present study was designed to evaluate the antioxidant, analgesic, and anti-inflammatory activities ofthe methanolic extract of Piper betle leaves (MPBL). Materials and Methods: MPBL was evaluated for anti-inflammatory activity using carrageenan-induced hind paw edema model. Analgesic activity of MPBL was evaluated by hot plate, writhing, and formalin tests. Total phenolic and flavonoids content, total antioxidant activity, scavenging of 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical, peroxynitrate (ONOO-) as well as  inhibition of total ROS generation, and assessment of reducing power were used to evaluate antioxidant potential of MPBL. Results: The extract of MPBL, at the dose of 100 and 200 mg/kg, produced a significant (