A single watermark based scheme for both protection and authentication of identities

The security of a watermarking scheme is mainly categorised as either robust or fragile. The former can withstand an authorised alteration/attack, primarily used in copyright protection. The latter follows a zero tolerance towards any modification, used primarily in content authentication processes. The existing literature in the field projects that two separate watermarks are required to make a watermarking scheme robust and fragile, thus making the overall process cumbersome and complex. A novel image watermarking scheme that uses only one watermark while achieving both goals of copyright protection and authentication of identities is presented. An unconventional concept of checkpointing is introduced, which equips the proposed scheme to be either robust or fragile, making it superior in its application versatility. First, watermark embedding within the host/original image is achieved by a combination of transform domain techniques along with a novel median-based embedding block selection procedure. Second, checkpointing is performed in the spatial domain. The watermarked image in the absence of an attack is correlated to the one that is being attacked, using the template energy comparison-based approach. In the case of the robust watermark, such checkpointing can establish whether the carried out attack is authorised or not, determining the successful recovery of the watermark or vice-versa. Moreover, in the case of the fragile watermark, a sole confirmation of the occurrence of an attack is sufficient to make the watermark recovery impossible. Finally, the experimental analysis of the proposed scheme illustrates its excellent performance and superiority over state-of-the-art methods within the field

A dual watermarking scheme for identity protection

A novel dual watermarking scheme with potential applications in identity protection, media integrity maintenance and copyright protection in both electronic and printed media is presented. The proposed watermarking scheme uses the owner’s signature and fingerprint as watermarks through which the ownership and validity of the media can be proven and kept intact. To begin with, the proposed watermarking scheme is implemented on continuous-tone/greyscale images, and later extended to images achieved via multitoning, an advanced version of halftoning-based printing. The proposed watermark embedding is robust and imperceptible. Experimental simulations and evaluations of the proposed method show excellent results from both objective and subjective view-points

A novel multipurpose watermarking scheme capable of protecting and authenticating images with tamper detection and localisation abilities

Technologies that fall under the umbrella of Industry 4.0 can be classified into one of its four significant components: cyber-physical systems, the internet of things (IoT), on-demand availability of computer system resources, and cognitive computing. The success of this industrial revolution lies in how well these components can communicate with each other, and work together in finding the most optimised solution for an assigned task. It is achieved by sharing data collected from a network of sensors. This data is communicated via images, videos, and a variety of other signals, attracting unwanted attention of hackers. The protection of such data is therefore pivotal, as is maintaining its integrity. To this end, this paper proposes a novel image watermarking scheme with potential applications in Industry 4.0. The strategy presented is multipurpose; one such purpose is authenticating the transmitted image, another is curtailing the illegal distribution of the image by providing copyright protection. To this end, two new watermarking methods are introduced, one of which is for embedding the robust watermark, and the other is related to the fragile watermark. The robust watermark's embedding is achieved in the frequency domain, wherein the frequency coefficients are selected using a novel mean-based coefficient selection procedure. Subsequently, the selected coefficients are manipulated in equal proportion to embed the robust watermark. The fragile watermark's embedding is achieved in the spatial domain, wherein self-generated fragile watermark(s) is embedded by directly altering the pixel bits of the host image. The effective combination of two domains results in a hybrid scheme and attains the vital balance between the watermarking requirements of imperceptibility, security and capacity. Moreover, in the case of tampering, the proposed scheme not only authenticates and provides copyright protection to images but can also detect tampering and localise the tampered regions. An extensive evaluation of the proposed scheme on typical images has proven its superiority over existing state-of-the-art methods

Design and delivery of a subject in robotics

Course design in engineering should be able to address the core competencies that are required by the engineering profession. To implement this concept many courses are structured to include real-situation projects. From the view point of mechatronic engineering education, it is clear that a robotic project will be suitable to integrate the course contents. However, to provide necessary theoretical skills for students to solve real engineering problems, project only is not sufficient in the subject. In this paper the design and delivery of a subject in robotics at the University of Western Sydney (UWS) is presented and discussed. In particular, this paper reviews the concept behind the course contents, assessments and delivery design. The paper has also demonstrated the impact of such course design in student performance and perception using student survey results and final grades in classes

Chroma based colour enhancement for improved colour segmentation

There are many applications rely on the use of colour segmentation in image processing. The major challenge with colour segmentation is that there is no unique solution as each person perceives and segments the colours in images differently. The segmentation results are also heavily influenced by environment factors such as lighting conditions and noise levels. In addition, existing methods tend to focus on the segmentation stage alone and employ little to none for pre-processing. Thus it can be a challenge task to develop an efficient colour segmentation method. In this paper, a novel colour enhancement method is introduced to boost the colour saliency of the critical regions and to improve the consistency of segmentation results by maximizing chroma while preserving hue. Tests in various common colour models using Euclidean distance segmentation method have shown that images pre-processed with the novel colour enhancement method produced much more accurate and reliable colour segmentation results than images without the enhancement or enhancement using existing methods

Human detection using gradient maps and golden ratio

Human detection is an important topic that can be used for many applications, it is mainly found in areas that required surveillance such as airports, casinos, factories, construction and mining sites. In this paper, a novel human detection method is introduced to extract the human figure from an input image without prior information or training. This method firstly uses a head and shoulder detection scheme based on curve detection with scaled gradient magnitude and orientation maps. It is then followed by a human body estimation scheme based on gap detection and golden ratio. Finally, the human figure is extracted through thresholding local gradient magnitude regions and horizontal filling. Tests on various images have shown that this method is capable of detecting and extracting human body figures robustly from different images

Detection of fillet weld joints using an adaptive line growing algorithm for robotic arc welding

One of the main challenges for robotic welding in low to medium volume manufacturing or repair work is the time taken to programme the robot path for a new job. It is often cheaper and more efficient to weld the parts manually. There are many papers published on the detection of butt welds, however there is no mature method for the identification of fillet welds which are more common. This paper presents a novel method that can autonomously identify fillet weld joints regardless of the base material, surface finish and surface imperfections such as scratches, mill scale and rust. The new method introduces an adaptive line growing algorithm for robust identification of weld joints regardless of the shape of the seam. The proposed method is validated through experiments using an industrial welding robot in a workshop environment. The results show that this method can detect realistic fillet weld joints for industrial arc welding applications

Image segmentation using adaptively selected color space

Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces is presented and a segmentation strategy is introduced to select the most effective space in which the segmentation result could be improved. Experimental results show that the proposed method can provide robust segmentation outcomes subject to parts with different colors and under different illumination conditions

A low cost hand-eye calibration method for arc welding robots

Hand-eye calibration is one of the most important and fundamental tasks in performing visual guided robot control tasks. Many techniques have been proposed that use various expensive equipment ranging from a three dimensional positioning device to a laser measurement device. The work presented in this paper aims at developing a low cost robot hand/eye calibration method that is accurate and robust enough to be used in a robotic arc welding system. The proposed calibration method allows the camera and object frames to be referenced directly to the robots base co-ordinate frame. Experimental results show that the developed method can be used to achieve a calibration accuracy of 1 mm (in the directions of interest, X and Y axes) that is acceptable for robotic welding applications

Colour identification using an adaptive colour model

Colour identification is a common task for many applications in computer vision. Many existing colour identification methods are application dependent. Therefore, they could only operate in certain environments and their performances are highly dependent on the lighting condition and quality of the images. In this paper, a novel colour identification method is introduced using an adaptive hue based colour model. The proposed method firstly analyses the image by collecting a variety of information from the given image. It is then followed by a colour space selection scheme in which the most suitable hue based colour space is selected based on properties obtained through image analysis. Finally, the image is filtered through the channels of the selected colour model to identify the target colour. Tests on various images from different datasets have shown that this method is capable of extracting the required colour effectively from images with varying qualities