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AN ANALYTICAL APPROACH OF SOLVING LIMITATION OF IMAGE MOSAICING BY IMAGE INPAINTING: AN EFFICIENT METHODOLOGY
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Upasana Jani, Kamal Sutaria
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Generally, we are facing the problem when we want to capture the same thing what we seen. But in the real life, the range of the image capturing device is smaller than the scene which is sense by eye. Even when try made for image capturing in single exposure it may result in image in which small data is not available or it is available then also they are blurred or it is also possible that we loss some part of information. In such a problem the only situation can be that get the different spilt images of same object and then stitch it that is mosaiced it. If there is not very careful photography some part is missed in rectangle image and this mosaiced image may result with black patches, which omit aim of mosaicing to merge image seamlessly. So the possible approach is to fill this missing part with the help of image completion concept which is image inpainting. The proposed methodology gives a analytical approach is to generate the image in such a way that the person who is not familiar with that place or object will consider it as original image. The aim of proposed methodology is to remove artefacts of the image mosaicing....
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SURVEY OF IMAGE COMPRESSION AND FACE RECOGNITION
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Vineet Bhatt*, K C Petwal
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This manuscript is related to use of linear algebra called “SVD” to digital image processing. We investigate the use of SVD in digital image processing for image compression and face recognition. Singular value decomposition method can transpose a matrix intoUSV^t, which is use to refactoring a digital image in three matrices. The using ofsingular values of such refactoring allows us to represent the image with a smaller set of values, whichcan preserve useful features of the original image, but use less storage space in the memory, and achieve the image compression process. For image compression by SVD, we will do an experiment on a digital image with the help of MATLAB code. We will use different singular values for compression of image and evaluate different compression ratio and quality measurement for best compression. To perform face recognition with SVD, we treated the set of known faces as vectors in a subspace, called “facespace”, spanned by a small group of “basefaces”. The projection of a new image onto the baseface is then compared to the set of known faces to identify the face. All tests and experiments are carried out by using MATLAB as computing environment and programming language....
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DESIGN OF EFFICIENT LANE DETECTION SYSTEM FOR DRIVER ASSISTANCE
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Ritesh J Bagde*, S S Wankhede
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A lane detection technique has become a interesting research topic in the field of vehicular electronics and in Intelligent Transportation System for driver safety. This paper presents a system for road lane detection using a test video recorded at Highway . The video is input to the system and after processing gives the lane detected video. The lanes are detected by the use of edge detection and Hough transform and fitted to the Kalman filter for tracking and smoothing. The propose algorithm can be used to detect the lane on road....
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REMOTELY SENSED IMAGE RETRIEVAL BASED ON REGION-LEVEL SEMANTIC MINING
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Tingting Liu, Liangpei Zhang, Pingxiang Li, Hui Lin
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As satellite images are widely used in a large number of applications in recent years, content-based image retrieval
technique has become important tools for image exploration and information mining; however, their performances
are limited by the semantic gap between low-level features and high-level concepts. To narrow this semantic gap,
a region-level semantic mining approach is proposed in this article. Because it is easier for users to understand
image content by region, images are segmented into several parts using an improved segmentation algorithm,
each with homogeneous spectral and textural characteristics, and then a uniform region-based representation for
each image is built. Once the probabilistic relationship among image, region, and hidden semantic is constructed,
the Expectation Maximization method can be applied to mine the hidden semantic. We implement this approach
on a dataset consisting of thousands of satellite images and obtain a high retrieval precision, as demonstrated
through experiments....
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SIMILARITY MEASURE FOR IMAGE RESIZING USING SIFT FEATURE
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Shungang Hua, Guopeng Chen, Honglei Wei, Qiuxin Jiang
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On the basis of the Scale Invariant Feature Transform (SIFT) feature, we research the distance measure in the
process of image resizing. Through extracting SIFT features from the original image and the resized one,
respectively, we match the SIFT features between two images, and calculate the distance for SIFT feature vectors to
evaluate the degree of similarity between the original and the resized image. On the basis of the Euclidean
distance measure, an effective image resizing algorithm combining Seam Carving with Scaling is proposed. We first
resize an image using Seam Carving, and calculate the similarity distance between the original image and its
resized one. Before the salient object and content are damaged obviously, we stop Seam Carving and transfer
residual task to Scaling. Experiments show that our algorithm is able to avoid the damage and distortion of image
content and preserve both the local structure and the global visual effect of the image graciously....
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SCREENSHOT IDENTIFICATION BY ANALYSIS OF DIRECTIONAL INEQUALITY OF INTERLACED VIDEO
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Ji-Won Lee, Min-Jeong Lee, Hae-Yeoun Lee, Heung-Kyu Lee
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As screenshots of copyrighted video content are spreading through the Internet without any regulation, cases of
copyright infringement have been observed. Further, it is difficult to use existing forensic techniques for
determining whether or not a given image was captured from a screen. Thus, we propose a screenshot
identification scheme using the trace of screen capture. Since most television systems and camcorders use
interlaced scanning, many screenshots are taken from interlaced videos. Consequently, these screenshots contain
the trace of interlaced videos, combing artifacts. In this study, we identify a screenshot using the characteristics of
combing artifacts that appear to be shaped like horizontal jagged noise and can be found around the edges. To
identify a screenshot, the edge areas are extracted using the gray level co-occurrence matrix (GLCM). Then, the
amount of combing artifacts is calculated in the extracted edge areas by using the similarity ratio (SR), the ratio of
the horizontal noise to the vertical noise. By analyzing the directional inequality of noise components, the
proposed scheme identifies the source of an input image. In the experiments conducted, the identification
accuracy is measured in various environments. The results prove that the proposed identification scheme is stable
and performs well....
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