Comparing Segmentation Quality of Real-Time Image Segmentation Techniques Using Metrics
Keywords:
Image segmentation, foreground segmentation, Precision, Recall, F1-score, AccuracyAbstract
The roles of real-time image segmentation and matching are of utmost importance, requiring the utilisation of efficient algorithms to promptly and precisely analyze images. The main goal of this research is to explore the procedure of obtaining real-time images from video footage using a camera, followed by the selection of a random image frame for the purpose of segmentation. Nevertheless, a notable obstacle arises when calculating metrics like Precision, Recall, F1 score, Accuracy, and SSIM by utilizing the segmented image and the Ground Truth image. To address these problems, a range of segmentation approaches are assessed in terms of their efficacy in computing the metrics described above. The segmentation technique employed in this study is the proposed method, which yields segmented images that exhibit successful outcomes. The paper presents a suggested methodology to augment the metrics of Precision, Recall, F1 score, Accuracy, and SSIM.
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