**6. Conclusion and future work**

In this study, a fast and effective method is proposed for hair-occluded removal in dermoscopic images. The implementation of the hair removal process is divided into two main stages: hair detection and inpainting. In hair detection, a morphological bottom-hat operation is implemented on Y-channel image of the YIQ color space followed by a binarization operation. In inpainting, the repaired Y-channel is partitioned into 256 non-overlapped blocks and for each block, white pixels are

*An Efficient Block-Based Algorithm for Hair Removal in Dermoscopic Images DOI: http://dx.doi.org/10.5772/intechopen.80024*

replaced by locating the highest peak of using a histogram function and a morphological close operation.

Our achieved results indicate high accuracy, and the proposed method can be dedicated to Dermatologists as a pre-processing stage before the lesion segmentation and classification. However, our proposed algorithm reports a true positive rate (sensitivity) of 97.36%, a false positive rate (fall-out) of 4.25%, and a true negative rate (specificity) of 95.75%. The diagnostic accuracy achieved is recorded at a high level of 95.78%.

The following opportunities are suggested for future work:

