Feature Extraction Techniques

Author(s):  
Heba Ahmed Elnemr ◽  
Nourhan Mohamed Zayed ◽  
Mahmoud Abdelmoneim Fakhreldein

The feature extraction is the process to represent raw image in a reduced form to facilitate decision making such as pattern detection, classification or recognition. Finding and extracting reliable and discriminative features is always a crucial step to complete the task of image recognition and computer vision. Furthermore, as the number of application demands increase, an extended study and investigation in the feature extraction field becomes very important. The goal of this chapter is to present an intensive survey of existing literatures on feature extraction techniques over the last years. All these techniques and algorithms have their advantages and limitations. Thus, in this chapter analysis of various techniques and transformations, submitted earlier in literature, for extracting various features from images will be discussed. Additionally, future research directions in the feature extraction area are provided.

Author(s):  
Sicheng Zhao ◽  
Guiguang Ding ◽  
Qingming Huang ◽  
Tat-Seng Chua ◽  
Björn W. Schuller ◽  
...  

Images can convey rich semantics and induce strong emotions in viewers. Recently, with the explosive growth of visual data, extensive research efforts have been dedicated to affective image content analysis (AICA). In this paper, we review the state-of-the-art methods comprehensively with respect to two main challenges -- affective gap and perception subjectivity. We begin with an introduction to the key emotion representation models that have been widely employed in AICA. Available existing datasets for performing evaluation are briefly described. We then summarize and compare the representative approaches on emotion feature extraction, personalized emotion prediction, and emotion distribution learning. Finally, we discuss some future research directions.


2009 ◽  
Vol 26 (1) ◽  
pp. 46-69
Author(s):  
Shamas-Ur-Rehman Toor

Management from Islamic Perspectives (MIP) is an emerging field that has begun to attract scholarly attention. However, the research undertaken so far has been rather fragmented and lack a clear agenda. This paper presents a literature review of the field and the areas of current focus. Although the field has a huge growth potential, I argue that it faces several challenges and problems as it develops further. I outline these potential pitfalls, suggest how to develop MIP as a formal discipline, and explain how to integrate it within real-life business practices. The article closes with a call for research to be conducted in a more organized fashion through an international consortium of researchers as well as recommendations for future research directions.


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