اسلامی مملکت کے بین الاقوامی تعلقات عصرحاضر کے تناظر میں

Islam where considers the superiority of law, provision of justice and equity, building and purification of civilization and emphasis on the welfare of society, there ensures the first priority to humanity, peace and prosperity in the external relations. Islamic state keeps relations on the basis of equality with the world and non-Muslim citizens living within the state. On this belief and ideology Islam invites the world to set together. Islam on these principles of Islamic ideology and belief sets the foundation of collectiveness. On this principle the whole philosophy of life and living system are embraced, and the same Islamic law is the foundation of nations, on this behalf the Islamic state organized the relation with other states. In this way Islamic state on these principles keep relations with other states and within the state relations between Muslim and non-Muslim citizens on the basis of brotherhoods, equality, mercy and the principles of dignity of human being. Along with peace Islam set the principles of war which comprise ethical and prison limitations, duties and ethics amongst warrior, difference between the rights of fighters and non-fighters, treatment with pact holders and prisoners, and specified the way of better treatment with the defeated nations. He thought the manners of war to bloody man who consider everything right during the war. Islam lays great stress on equality, social justice, brotherhood and peace not only in state but across the boarders too. In this article a deep study is done to explain the relations of an Islamic state with other states. Islamic foreign policy emphasizes on the principles of equality among all the human beings and all the races and nations. Islam builds international relation on humanitarian basis.

Facial Expression Recognition in Unconstrained Environment

Facial expressions are the most effective form of non-verbal communication which is used to express one’s emotions. It not only expresses our expressions, but also communicates a wealth of information during social interaction. Facial expressions play an important and effective role in Human-Computer Interaction. Unlike humans, facial expression recognition is a challenging task for computers and research work in this domain can still be considered in seminal form. The prevalent facial expression techniques tend to provide accurate and impressive results for the images captured under controlled environment with a cooperative subject. However, majority of these techniques fail to provide adequate results for the images captured in uncontrolled environment. Achieving a higher classification accuracy rate for the images captured in uncontrolled environments is a major challenge being faced by researchers in this domain. There are many factors such as illumination, image orientations, noise and low-resolution, which hinder the development of facial expression recognition system in uncontrolled environment. Even the datasets prepared under the constrained environments sometimes need preprocessing before the classification stage. The core objective of this dissertation is to analyze existing techniques and develop an effective framework that is capable of classification of human facial expressions both under constrained and unconstrained environments. In this dissertation, we have explored, investigated and proposed frameworks to deal with two of the most common, influential and challenging issues that affect the accuracy of a facial expression recognition for images captured in an uncontrolled environment, namely illumination and low-resolution. First, a novel framework for feature extraction named Weber Local Binary Image Cosine Transform has been developed which not only extracts significant features by integrating features extracted using local binary pattern and weber local descriptor but also utilizes most discriminant features by applying the frequencybased components. Low-resolution and multi-orientation facial images have been used for the classification and a significant improvement in the classification accuracy rate has been achieved with the proposed framework. The developed framework has proved to be not only reliable but also computationally efficient across multiple datasets in the presence of noise and orientations. The Proposed framework has been tested on four datasets including JAFEE, MMI, CK+ and SFEW datasets. The second major contribution is the development of an illumination invariant technique. The proposed framework has been named Weber Local Binary Image Cosine Transform (WLBI-CT) and it advocates for the need of simultaneous contrast enhancement and brightness preservation for datasets containing real world images in unconstrained environment. The empirical results for the SFEW dataset are promising. In order to evaluate the performance of the proposed framework, rigorous set of experiments are presented in this thesis. The empirical results meet the standard quantitative measure criteria. The comparison of our work with various other stateof-the-art techniques is also presented using various benchmarks for these factors. The results are impressive even in the case of inclusion of noise and occlusion effects.