Images, in contrast to text, represent an effective and natural communication media for humans, due to their immediacy and the easy way to understand the image content. Shape recognition and pattern recognition are one of the most important tasks in the image processing. Crime scene photos should always be in focus and there should always be a ruler be present, this will allow the investigators the ability to resize the image to accurately reconstruct the scene. Therefore, the camera must be on a grounded platform such as tripod. Due to the rotation of the camera around the camera center there exist the distortion in the image which must be minimized. The distorted image should be corrected using transformation method. Deze taak is nogal uitdagend en essentieel omdat elke verandering in de afbeeldingen kan misidentificeren een object voor onderzoekers. Forensic image processing can help the analyst extract information from low quality, noisy image or geometrically distorted. Obviously, the desired information must be present in the image although it may not be apparent or visible. Considering challenges in complex forensic investigation, we understand the importance and sensitivity of data in a forensic images.The HT is an effective technique for detecting and finding the images within noise. It is a typical method to detect or segment geometry objects from images. Specifically, the straight-line detection case has been ingeniously exploited in several applications. The main advantage of the HT technique is that it is tolerant of gaps in feature boundary descriptions and is relatively unaffected by image noise. The HT and its extensions constitute a popular and robust method for extracting analytic curves. HT   attracted a lot of research efforts over the decades. The main motivations behind such interest are the noise immunity, the ability to deal with occlusion, and the expandability of the transform. Many variations of it have evolved. They cover a whole spectrum of shape detection from lines to irregular shapes. This master thesis presents a contribution in the field of forensic image processing. Two different approaches, Hough Line Transformation (HLT), Hough Circular Transformation (HCT) are followed to address this problem. Fout estimatie en validatie is gedaan met de hulp van root mean square method. De prestatie van beide methoden is geëvalueerd door ze te vergelijken. We present our solution as an application to the MATLAB environment, specifically designed to be used as a forensic tool for forensic images.

Background: The circular economy has emerged as an alternative to linear approaches to consumption and has the potential to solve the most pressing sustainability issues society faces today. SMEs have a central role in the transition towards a circular economy, as they make up the majority of businesses in Europe. However, the adoption of circular practices has been slower than expected. Researching what is affecting the adoption of these practices could provide answers and insights into how to accelerate this transition.  Purpose: The purpose of this study is to explore the role of organizational climate as a moderator when implementing circular business practices, given its potential to lead to organizational change.  Method: This study follows an interpretive approach through a multiple exploratory case study using two companies. Qualitative semi-structured interviews and observations from the company visits were used as primary data. The empirical data is analyzed through a general coding procedure, where explanation building was used as the approach. The research adds to existing theory through an abductive approach.   Conclusion: By exploring the challenges people face in SMEs, we have found that the organizational climate of the company is a critical factor that can affect the implementation of circular practices. Therefore, we propose that by creating the right climate, organizations could potentially accelerate this transition.

This work is focused on automatic detection of optic disc in retinal images. There is briefly described anatomy of human eye, principles of retinal imaging and also overview of the methods used for optic disc detection. The practical part describes developed procedures for optic disc detection, ie detection based on watershed transform, active contours and also on region growing technique. The main method of this work is the method of circular transformation, which as the only one allowed to detect the optic disc on the images of video ophtalmoscope and also on the high quality images from fundus cameras. This method was tested on three datasets. The average overlap 92,44 % was achieved for HRF dataset, 91,03 for DRIONS dataset and 77,36 for images of video ophtalmoscope.

Global consumption levels currently extend far beyond what planet Earth in terms of natural resources can regenerate in a sustainable manor and will by 2050 reach levels corresponding to what it would require three Earths to sustain. This overexploitation and unsustainable management of the Earth’s resources in combination with the necessity of mitigating climate change and reaching net zero CO2 emissions by 2050 require action across all sectors, not least the manufacturing industry. This thesis covers how large manufacturing enterprises can implement and utilize strategic targets and Key Performance Indicators (KPIs) to align with the principles of a Circular Economy (CE), and as a result, improve sustainability and business performance. Based on a case study conducted at Siemens Energy (SE) involving a literature study, interview study, and focus groups, a carefully selected set of strategic circularity targets and KPIs are presented to measure, evaluate, and drive circularity performance within large manufacturing enterprises. Since the thesis’ ambition was to provide valuable insights beyond SE, strategic circularity targets and KPIs specifically directed at SE were further generalized to be universally relevant for academia and other large manufacturing enterprises. Enterprises within the given sector share several key characteristics such as extensive material resource flows and complex value chains, hence strategic targets and KPIs emphasize material efficiency through decreasing virgin material dependency, increasing recirculation rates, and transitioning towards circular business models. While suggested targets and KPIs are universally directed at large manufacturing enterprises, individual organizations are recommended to conduct internal investigations and analyzes to further tailor and adapt strategic targets and KPIs towards the specific enterprise. In addition to strategic targets and KPIs, the thesis also presents an overview of opportunities, benefits, risks, and potential impacts for large manufacturing enterprises aspiring to increase circular initiatives, highlighting key principles to manage risk and capitalize on opportunities. The findings conclude that the main opportunity enabled by CE is to leverage synergies which align environmental, economic, and strategic corporate incentives, with key benefits including aspects such as decarbonization and reduced environmental impact, increased revenues and cost savings, risk management, and new business opportunities. Risks associated with CE include rebound effects, organizational insufficiencies, lack of material quality and safety, as well as a low product performance, which further can lead to potential impacts mitigating the positive effects of CE, or at worst setbacks causing a net negative output from implemented circular measures. In summary, the opportunities and benefits associated with CE are many, but implemented circular measures require risk awareness and continuous management to ensure efficiency.