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The computer based mammogram image analysis focuses on the classification of the images into either benign, malignant or normal based on the features of the identified and segmented masses / lesions. This task remains as a challenge, when the size of Region of Interest is very small and the contrast / brightness of the images is not optimum. The image enhancement techniques greatly help to distinguish...
Clouds inhibit the features of images such as color and brightness in the image regions. The light diffusion, scattering and attenuation of clouds create blur effect or affect the contrast of the images. The interference of cloud over images degrades the quality of satellite images and tends to suppress the essential information in those images. Hence, the removal of clouds greatly help in the efficient...
We present the performance of three popular image feature extraction methods such as Scale Invariant Feature Transformation (SIFT), Speeded-Up Robust Features (SURF) and Histogram of Oriented Gradient (HOG). Specifically, we compare the performance of feature detection methods for images corrupted with different types of noise. The efficiency of three methods are measured by considering number of...
Automatic monitoring of the region using single stationary camera had become a vital part of the surveillance. The tracking of moving objects can undergo limitations such as illumination variation, camera noise, occlusion. Many methods exist to overcome this limitation. In the multiple moving object system detection is done by using Mixture of Gaussian based on background subtraction to get foreground...
In this paper, heuristic algorithm assisted multi-thresholding is attempted for standard RGB test images using Kapur's entropy. The motivation of this work is to present a detailed assessment among the Brownian search based heuristic approaches, such as bacteria foraging optimization, firefly algorithm, and cuckoo search. Proposed technique is implemented and validated on frequently used benchmark...
The paper proposes a workflow for the automatic detection of anomalous behavior in an examination hall, towards the automated proctoring of tests in classes. Certain assumptions about normal behavior in the context of proctoring exams are made. Anomalies are behavior patterns that are relatively (and significantly) different. While not every anomalous behavior may be cause for suspicion, the system...
Image retrieval and classification in medical domain are the two important aspects in decision making and automatic annotation of benign and malignant images. These processes improve the decision making during decease identification. Image classification is usually done by checking image visual or semantic content similarity. Image content may be represented by its low level visual features referring...
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