Journal of Image Processing & Pattern Recognition Progress
Volume 4, Issue 3 (2017)
Published
Table of contents
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A Novel Segmentation Method of Cervical Cancer affected Surface Tissues based on Superpixels
Abstract: AbstractCervical Cancer is one of the pervasive forms of cancer afflicting the female population worldwide. A Digital Colposcope is a self-illuminated powerful microscope which acquires the image of the affected cervix. The raw cervix image acquired by the colposcope is known as a cervigram. The raw cervigram is preprocessed by removing the specular reflections and then the region of interest is sought. Different novel segmentation algorithms which were proposed in …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 1–7 Read article
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A Parallel Unit Encoding Stage for BCWT using GPGPU
Abstract: AbstractA backward coding of wavelet trees (BCWT) algorithm begins the coding process from the lower-level to the higher-level of the wavelet tree. While processing, it builds up the maximum quantization levels of the descendant (MQD) map and maximum quantization level (MQL) by the support of the wavelet coefficients of the corresponding image. In the processes of making the serial encoding stages into parallel stages, primarily we deal with a prominent …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 13–23 Read article
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CBIR Using Various Approaches: A Review
Abstract: AbstractContent based image retrieval (CBIR) is important technique for finding various images from a huge amount of image database. So, picture hunt and recovery from extensive picture informational collection is difficult task. CBIR utilizes the picture visual contents for instance shading, shape and surface to list and speak to picture. In this paper, all the methods of color, texture and shape features removal is described. Researchers can combine one of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 24–30 Read article
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Colour Based Segmentation of a Landsat Image Using K-Means Clustering Algorithm
Abstract: AbstractImage segmentation is one of the typical vintage subjects in image processing and it acts as a bulls-eye of the image processing technique. By definition, image segmentation means identifying the similar regions in the image; or in other words, identifying the homogenous pixels in the image and grouping all these pixels based on the homogeneity condition considered. This homogeneity condition can be like, colour, texture, size, compactness etc. It is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 31–38 Read article
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Contrast Image Enhancement Using Various Approaches: A Review
Abstract: AbstractImage enhancement is one of the most key issues in high quality pictures such as digital cameras and image research area. Since picture readability may be very effortlessly affected because of lighting fixtures during image acquiring, climate, or other equipment that has been used to seize the picture. These conditions may lead to image suffering from poor contrast and noise. Contrast enhancement converts the pixels depth of the input picture …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 39–45 Read article
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Lossy Image Compression Using Exponential Growth Equation and Encryption by Natural Exponential Function
Abstract: AbstractImage compression is an essential technology in transmission and storage of digital images because of vast data associated with them. So, image compression plays an important role in the transmission of digital images through the internet with less bandwidth and occupies less space in memory. This research suggests a new image compression method based on exponential growth equation. The exponential growth equation is used for the image compression. The effectiveness …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 46–55 Read article
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Plant Disease Detection Using SVM
Abstract: AbstractDiseases in plants are responsible for major production and economic losses and also reduction in yield. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself, it detects the symptoms of diseases. Detection on plant is very critical for defensible agriculture. It is very challenging to monitor the plant diseases physically. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 8–12 Read article