TY - JOUR ID - 1581 TI - Segmentation Assisted Object Distinction for Direct Volume Rendering JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Azimzadeh Irani, A. AU - Pourgholi, R. AD - School of Mathematics and Computer Science, Damghan University, Damghan, Iran. Y1 - 2020 PY - 2020 VL - 8 IS - 1 SP - 67 EP - 82 KW - Hybrid image segmentation KW - Volume rendering KW - Enhanced visualization effect DO - 10.22044/jadm.2019.7207.1854 N2 - Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an image processing based approach towards enhancing ray casting technique for object distinction process. The rendering mode is modified to accommodate masking information generated by a K-means based hybrid segmentation algorithm. An effective set of image processing techniques are creatively employed in construction of a generic segmentation system capable of generating object membership information. UR - https://jad.shahroodut.ac.ir/article_1581.html L1 - https://jad.shahroodut.ac.ir/article_1581_808db24af54ab94eeaac67adfb6d51f7.pdf ER -