A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

Application of morphometry, static DNA ploidy analysis, and steroid receptor expression in diagnosis and prognosis of Libyan breast cancer

The aim of this study was to describe the demographic, clinicopathological, biological and morphometric features of Libyan breast cancer patients. The supporting value of nuclear morphometry and static image cytometry in the sensitivity for detecting breast cancer in conventional fine-needle aspiration biopsies were estimated. The findings were compared with findings in breast cancer in Finland and Nigeria. In addation, the value of ER and PR were evaluated. There were 131 histological samples, 41 cytological samples, and demographic and clinicopathological data from 234 Libyan patients. The Libyan breast cancer is dominantly premenopausal and in this feature it is similar to breast cancer in sub-Saharan Africans, but clearly different from breast cancer in Europeans, whose cancers are dominantly postmenopausal in character. At presention most Libyan patients have locally advanced disease, which is associated with poor survival rates. Nuclear morphometry and image DNA cytometry agree with earlier published data in the Finnish population and indicate that nuclear size and DNA analysis of nuclear content can be used to increase the cytological sensitivity and specificity in doubtful breast lesions, particularly when free cell sampling method is used. Combination of the morphometric data with earlier free cell data gave the following diagnostic guidelines: Range of overlap in free cell samples: 55 μm2 -71 μm2. Cut-off values for diagnostic purposes: Mean nuclear area (MNA) >54 μm2 for 100% detection of malignant cases (specificity 84 %), MNA < 72 μm2 for 100% detection of benign cases (sensitivity 91%). Histomorphometry showed a significant correlation between the MNA and most clinicopathological features, with the strongest association observed for histological grade (p <0.0001). MNA seems to be a prognosticator in Libyan breast cancer (Pearson’s test r = - 0.29, p = 0.019), but at lower level of significance than in the European material. A corresponding relationship was not found in shape-related morphometric features. ER and PR staining scores were in correlation with the clinical stage (p= 0.017, and 0.015, respectively), and also associated with lymph node negative patients (p=0.03, p=0.05, respectively). Receptor-positive (HR+) patients had a better survival. The fraction of HR+ cases among Libyan breast cancers is about the same as the fraction of positive cases in European breast cancer. The study suggests that also weak staining (corresponding to as few as 1% positive cells) has prognostic value. The prognostic significance may be associated with the practice to use antihormonal therapy in HR+ cases. The low survival and advanced presentation is associated with active cell proliferation, atypical nuclear morphology and aneuploid nuclear DNA content in Libyan breast cancer patients. The findings support the idea that breast cancer is not one type of disease, but should probably be classified into premenopausal and post menopausal types.

University Image vs. University Identity: Congruence between Expectations and Experience

The aim of this thesis was to examine congruencies between university identity and university images of prospective and current students. Therefore, factors essentially influencing on expected and experienced university images were identified. Providing an understanding on the differences in the formation of both concepts allowed the analysis of potential incongruities between a university’s identity and the perceptions its students hold. The study was conducted in July and August 2013 at Lappeenranta University of Technology by means of a web-based research survey. The sample consisted of 160 international Master’s degree students who were admitted in 2011, 2012 and 2013. Descriptive and multivariate statistical analysis methods were used to process the data. The results of the study indicated statistically significant incongruities between the case university’s identity and its students’ images. Further, the expected and experienced university images showed incongruities to each other. Deviations were additionally detected to be dependent on the students’ home regions. All in all, there is potential for an improvement of the students’ experiences resulting from a low perception of the student’s preparation for future job life.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Omnibus accounts to Finnish investors? – An analysis of the costs and benefits that omnibus account structure brings to Finnish account operators and investors

The Finnish Securities Markets are being harmonized to enable better, more reliable and timely settlement of securities. Omnibus accounts are a common practice in the European securities markets. Finland forbids the use of omnibus accounts from its domestic investors. There is a possibility that the omnibus account usage is allowed for Finnish investors in the future. This study aims to build a comprehensive image to Finnish investors and account operators in determining the costs and benefits that the omnibus account structure would have for them. This study uses qualitative research methods. A literature review provides the framework for this study. Different kinds of research articles, regulatory documents, studies performed by European organisations, and Finnish news reportages are used to analyse the costs and benefits of omnibus accounts. The viewpoint is strictly of account operators and investors, and different effects on them are contemplated. The results of the analysis show that there are a number of costs and benefits that investors and account operators must take into consideration regarding omnibus accounts. The costs are related to development of IT-systems so that participants are able to adapt to the new structure and operate according to its needs. Decrease in the holdings’ transparency is a disadvantage of the structure and needs to be assessed precisely to avoid some problems it might bring. Benefits are mostly related to the increased competition in the securities markets as well as to the possible cost reductions of securities settlement. The costs and benefits were analysed according to the study plan of this thesis and as a result, the significance and impact of omnibus accounts to Finnish investors and account operators depends on the competition level and the decisions that all market participants make when determining if the account structure is beneficial for their operations.

Corporate green image communication through public disclosures and social media

Today, companies need to mind the environment in all their actions. Policies, regulations and growing pressure from environmentally conscious public are driving corporations to invest increasingly in their green images. Communication plays a key role in forming and maintaining that image. This thesis explores how six selected companies communicate about their environmental efforts and activities, and its linkage to their green images, in annual and sustainability reports and in Facebook. The companies come from the U.S. and Europe and operate in three different industries: ICT, oil and gas, and aerospace & defense. Qualitative and quantitative content analyses are conducted to examine 36 reports and 121 Facebook messages, collected from the period of 2010-2014, and from 2005 for comparison. The results show that although the quality and quantity of environmental disclosure is increasing, there is still room for improvement. Overall, disclosure in the ICT sector is on the highest level. The European companies disclose more and on average have stronger green images than the American ones. Emissions and ways to reduce them is by far the most covered topic in both continents and in all three industry sectors. The messages in Facebook are closer to advertising, and overall the platform is utilized surprisingly little.

Software for Transport Accessibility Analysis: The Case of Moscow

In this thesis the process of building a software for transport accessibility analysis is described. The goal was to create a software which is easy to distribute and simple to use for the user without particular background in the field of the geographical data analysis. It was shown that existing tools do not suit for this particular task due to complex interface or significant rendering time. The goal was accomplished by applying modern approaches in the process of building web applications such as maps based on vector tiles, FLUX architecture design pattern and module bundling. It was discovered that vector tiles have considerable advantages over image-based tiles such as faster rendering and real-time styling.