Journal of Image Processing & Pattern Recognition Progress
Volume 1, Issue 1 (2014)
Published
Table of contents
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Performance Comparison between Back-Propagation Learning and Kohonen Self-Organizing Neural Networks Algorithm in Terms of Pattern Recognition
Abstract: Pattern recognition using back-propagation learning and Kohonen self-organizing neural network algorithms has been developed and measured various performance based on different criteria and environment of the pattern. These pattern recognition systems have taken the object image as input. In image pre-processing stage, scaling and clipping process has been applied from the background image to avoid unnecessary portion of the object image. Feature extraction has been performed after applying filtering and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 1–8 Read article
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Image Segmentation based on Region Merging using Breadth-First Search
Abstract: This paper proposed a new method for image segmentation based on region merging using breadth-first search (BFS). The image can be partitioned into multiple segments so that meaningful information is extracted out and then image is analyzed easily. In the proposed method, first the oversegmented image is obtained by applying a standard watershed transformation on original image. Then BFS is executed on the oversegmented image to obtain a segmented image. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 20–25 Read article
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Q-Metrics for Early Detection of Cervical Cancer
Abstract: The most prevalent form of cancer in women worldwide is uterine cervical cancer. Through screening programs aimed at detecting precancerous lesions most cases of cervical cancer can be prevented. In this article, Q-metrics has been proposed for carrying out automated image segmentation of uterine cervical cancer. The validation of detection of cervical lesions is an important issue in medical image processing because it has a specific impact on surgical planning. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 26–30 Read article
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Region Segmentation and Annotation with Vehicle Detection Validation Application in Airborne Images
Abstract: In this work, the authors propose an automatic image segmentation and annotation system for airborne images. Initial region segmentation using existing region segmentation methods is applied to airborne images first. To deal with over-segmentation on the initial region segmentation results, the authors performed graph-based region merging by constructing an undirected-graph based on 8-connected local neighborhood. For each region, the authors extracted low-level features and used the Support Vector Machine (SVM) …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 9–19 Read article