International Journal of Image Processing and Pattern Recognition
Volume 4, Issue 1 (2018)
Published
Table of contents
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Compare Effect of Gaussian Noise on RBG Line
Abstract: Gaussian noise tends to come in digital images. It enters into images when there is low light condition or high light conditions. This paper deals with comparison of gaussian noise effect on red, green, blue line image by accounting Entropy, Signal to Noise Ratio, Peak Signal to Noise Ratio and Root Mean Square Error as performance parameters. This paper proves that Blue color is the least affected and green being …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 1–6 Read article
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Feature Extraction: Comparing Feature Extractors
Abstract: Machine learning is getting fuzz nowadays a lot. In order to train the computer to recognize the set of images is the key factor. For this neural networks and classifiers are used to do the identification and recognition. Now do the matching feature points or the interest points are required which makes it to our area of research i.e. feature extractors. In our paper we compared various feature extractors Fast, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 12–17 Read article
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Image Authentication Using Digital Watermarking: A Survey
Abstract: Watermarking has a place with the data hiding field, has seen a ton of research intrigue as of late. Principle necessity of the Watermark is that it must be vigorous and impalpable. Heartiness of watermark as for each picture twisting can be assessed as far as effective recuperation of watermark. In the wake of recouping the watermark, the recuperated and unique watermarks are looked at by ascertaining of similitude factor …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 18–30 Read article
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Artificial neural network based classification of varieties of thin and thick fabric images
Abstract: Abstract: The proposed work focuses on classification of varieties of thin and thick fabric materials from images. The morphological operations such as erosion and dilation are performed. Morphological features namely, avg_moments, average_area, roundness, max_area, average_perimeter, average_eccentricity, circularity and average_equivalent_diameter are extracted. The prediction is carried out using artificial neural network. The classification rates of 84.84% and 90.90% are obtained for thin and thick fabric images. The classification rates for varieties …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 31–41 Read article
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Computing Effect of Gaussian Noise on Pixels: Testing on Red Color Triangle
Abstract: Gaussian noise is the noise that effects the pixels of the image that are in the center i.e. its effect is due to change in light conditions. This paper tests the effect of gaussian noise on the red color image by graphically depicting the matrix representation of the image using mesh diagram in MATLAB. This paper proves that pixels in the center of the image are more affected when these …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 7–11 Read article