Segmentation of Thermal Images using Adaptive C means (ACM) technique for diabetic feet

Madhava Prabhu

Abstract


DFU (Diabetic Foot Ulcer) is one of the major concern and it is rapidly increasing, in worst case scenario this may lead for amputation. However, in several cases the DFU can be avoided by early detection and diagnosis. Several detection technique has been presented in order to detect the DFU. However, the detection fails to provide the absolute detection. The process used to detect the DFU is pre-processing, segmentation and feature extraction, segmentation is one of the challenging task. Hence, in this paper, we have presented the segmentation algorithm namely ACM (Adaptive C means) clustering for the image segmentation. ACM is based on the spatial information and this method includes the two stage.  In first stage nonlocal spatial information is added, in second stage spatial shape information is used in order to refine the constraint of local spatial and this in terms helps in refining the local spatial constraint. Outcome of the proposed method shows that ACM is very much effective and outperforms other existing method.


Keywords


Thermography; Segmentation; Diabetes; Adaptive; Image Processing

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DOI: http://doi.org/10.11591/ijece.v11i2.pp%25p
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