ICGST Journal of Graphics, Vision and Image Processing
|Journal Papers (2)||Details||Call for Paper||Manuscript submission||Publication Ethics||Contact||Authors' Guide Line|
|1 The State of the Art of Video Summarization for Mobile Devices: Review Article , Hesham Farouk and Kamal ElDahshan and Amr Abozeid
Video summarization is very important field to facilitate userís usage requirements, especially in the context of mobile computing and the need to access videos from anywhere at any time. This paper presents a study and evaluation of various video summarization techniques for mobile devices available in the literature from 2001 till the first half of 2014. The proposed evaluation criteria used here have been derived from the analysis of literatures and existing works in the domain of video summarization. We recommended cluster flower figure that can be used to depict a video summarization technique (more than 10 techniques covered) based on the proposed criteria (a set of 8 criteria applied). The advantage of this research is making a state of the art of the related works which help researchers in this context. Also, researchers can classify their works and determine the research opportunities based on the proposed criteria.
|2 Visual Perception Oriented CBIR envisaged through Fractals and Presence Score, Suhas S Rautmare and Anjali S Bhalchandra
The objective of this research is to validate the feasibility of successful content based image search using fractals. Fractal based approach has been embedded into one of the theories of visual perception of an image. An important function of selective visual attention is to direct our gaze rapidly towards objects of interest in our visual environment. Two distinct pathways in human visual perception for scene recognition are what pathway and where pathway. They work simultaneously to perceive scene as a whole. The proposed approach simulates human visual perception mechanism similar to that of the brain. The Hausdorff Fractals have been used in what pathway and Presence Score has been used in where pathway to generate a composite feature vector. The feature vector captures color, shape, texture information and significant region of interest of the image through fractals and presence score. In order to improve retrieval performance in the sense of accuracy and time, similar images are clustered together through maxdistnace and maxclustersize based clustering approach. The results obtained with an optimum sized feature vector are good enough to validate the approach and the conceptualized analogy between human and computer based image processing. The search has also been successfully extended using text annotation to web search through Google to provide wider coverage of CBIR