Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
An empirical approach to grouping and segmentation
An empirical approach to grouping and segmentation
Automatic Recognition of a Baby Gesture
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Toward Objective Evaluation of Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Segmentation Techniques Using Region Size and Boundary Information
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Color-Based Image Salient Region Segmentation Using Novel Region Merging Strategy
IEEE Transactions on Multimedia
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In many medical examinations, image or video based automatic schemes are preferred over conventional approaches. Such schemes can greatly increase the efficacy and accuracy of various medical examinations. The work proposed in this article presents an image processing based method to automate adductors angle measurement which is carried out on infants as a part of Hammersmith Infant Neurological Examination (HINE). It is used for assessing neurological development of infants aged below two years. During HINE, postures and reactions of the infant under consideration are recorded. An overall score is estimated and used to quantify the neurological development index of the baby. In the conventional approach, for measuring adductors angle, doctors use rulers. The proposed method uses image segmentation and thinning techniques to measure the angle without involvement of rulers. Results show that the proposed scheme can be used as an aid to the doctors for conducting such examinations.