This paper presents the methods to detect and segment lactiferous vessels or rubber latex vessels from gray scale microscopic cross-sectional images using polynomial curve-fitting with maximum and minimum stationary points. Polynomial curve-fitting is used to detect the location of lactiferous vessels from an image of a non-dyed cross-sectional slice which was taken by a digital camera through microscope lens. The lactiferous vessels are then segmented from an image using maximum and minimum stationary points with morphological closing operation. Two species of rubber trees of age between one to two years old are sampled namely, RRIM600 and RRIT251. Two data sets contain 30 microscopic cross-sectional images of one-year old rubber tree’s stems from each species are used in the experiments and the results reveal that most of the lactiferous vessel areas can be segmented correctly.
This paper proposes a novel method to generate keyframes from cartoon animation with the aim to improve the details
and accuracy of contents represented by keyframes. Consider that general techniques on video summarization usually
drop some important contents due to its restriction on aspect ratio; this paper thus proposes a new method using
panorama technology to add more details to be included in each keyframe. The concept is to mark the time code based
on shot boundary and optical flow direction. The period of time between every two consecutive marked time codes is
used to form a shot sequence which is actually a sequence of frames. The global and local optical flows are also used to
determine how to select the frames and when to stitch the frames together according to the rules. The results of this
proposed method are keyframes generated from various types of cartoon animation which are outstanding compared to
their comic adaptations.