• Swami Omprakash Channaveer
• Londhe Pranita
• Divekar Nitin

The work done here is base upon dispensation of blood microscopic images to be familiar with the Leukemia. According to different categorization of leukemia, this work focuses on the Leukemia and its types that have an effect on mostly the adult and children. Premature work is done by color change of the image from RGB to CIELAB color space to make the segmentation method perform well. In segmentation process, the widely used technique is K-means algorithm. K-means is an unsupervised knowledge algorithm based on clustering of similar performance of the objects. characteristic extraction technique include the Hausdorff dimension (HD) and Local Binary Pattern. Support Vector Machine is used for classification. The evaluation of various result analysis parameters is analyze to achieve precision.

Segmentation, K-means algorithm, Local Binary Pattern, Hausdorff Dimension, Support Vector Machine.

" Detection of Leukaemia in Microscopic Images Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.185-188, December-2018, Available :http://www.jetir.org/papers/JETIR1812529.pdf

" Detection of Leukaemia in Microscopic Images Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp185-188, December-2018, Available at : http://www.jetir.org/papers/JETIR1812529.pdf