Journal of Image Processing & Pattern Recognition Progress
Volume 2, Issue 1 (2015)
Published
Table of contents
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A Survey of Multiwavelet Filtering Based Denoising Techniques for Mammographic Medical Images
Abstract: The digital mammographic imagery is often influenced by various types of noises and thus requires application of various filters to denoise the noise level in order to preserve the vital imagery contents. This evidently helps the medical practitioner to improve the image quality of the mammograms and helps them in giving accurate diagnosis. We have presented a survey of the popular denoising techniques used in the literature to achieve the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 1–4 Read article
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Automatic Facial Recognition Using Adaptive Modelling of Illumination Field for Shape Recovery of Micro Facial Features
Abstract: In this study, we present an innovative framework to resolve the issue of confounding effects caused by variation of illumination in the scenario of face recognition. The proposed framework involves a mathematically modelled adaptive algorithm which augments the pixels sets of facial images with realistically simulated illumination field. This enhances the recognition rate and subsequently its performance in a way independent of classifier mode for each of its facial parameters. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 19–24 Read article
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Multispectral Image Denoising using Bi-Directional Recurrent Neural Network with DPCA Algorithm
Abstract: In practices, a Multispectral Images (MSI) image is always prone to corruption by various sources of noises while procuring the images. In this paper we implemented Decomposable Pixel Component Analysis (DPCA) algorithm with recurrent neural network (RNN) which effectively denoised the MSI images. The RNN enables shrinkage of non-reusable data points during DPCA execution and aid it to effectively transform spatial coordinate in a logical manner and reduces the time …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 25–30 Read article
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Emotion Recognition Through Image Processing for Improving Human Computer Interaction
Abstract: Detection and extracting various emotions and then validating those emotions from facial expression have become very important for improving the overall human-computer interaction. Emotion detection has several applications in areas such as artificial intelligence, image processing, intelligent Human-Computer interfaces. This paper reviews the literature on different aspects like different theories of emotions, methods of detecting emotions like face detection, eye detection, lip detection. This paper reviews comparative techniques for recognizing …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 31–35 Read article
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Detection of Facial Parts based on ABLATA
Abstract: Facial feature detection from standard 2D RGB images is a well-researched field but out of prolific techniques there isn't much efficacy is achieved in the previous studies that can extract feature data even for a low quality images in real time. Hence, we propose an algorithm based on Attribute Based Level Adaptive Algorithm (ABLATA) which use recursive data estimates for this task. While the recursive data estimates learns the relation …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 36–41 Read article
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NDVI An Indicator of Forest Cover Change Detection: A Geospatial Study on Chunati Forest Beat Areas, Chittagong, Bangladesh
Abstract: Chunati Forest Beat Areas (CFBA) consisting of seven reserved forest (RF) blocks/beats of hill forests is located in the countries south-eastern region is facing deforestation problem due to extensive logging and encroachment. Geospatial technology in combination with Remote Sensing and Geographical Information System (GIS) can be used to assess the change of vegetation cover of Chunati Forest Areas. For this study, false color composite of band 4, 3, and 2 …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 5–18 Read article