MODELISASI KOTAK TISU DENGAN PENGGABUNGAN KURVA BEZIER, KURVA HERMIT DAN HASIL DEFORMASI BENDA GEOMETRI

The tissue box is a place to store tissues to make them look neat and protect the tissues from dirt and dust. Tissue boxes are often used in households, restaurants and also as room decorations. Therefore, the shapes of tissue boxes that are being developed are increasingly varied according to consumer interests. The tissue box consists of three main parts, namely the cover, body and base of the box. This research was carried out by developing variations in the shape of the tissue box components using the Bezier curve, the Hermit curve and the results of the deformation of geometric objects. The deformation techniques used are rotation, dilation, and curve interpolation. Tissue box modeling processes are divided into four stages. The first, modeling the tissue box by dividing into three models, namely model A, model B and model C. The second, determining the size of the tissue box components based on the model. The third, modeling tissue box components. Finally, visualizing the results of the tissue box model by combining the components so that a variety of tissue box models are produced.

Data Analyzing via Probabilistic Modeling

Object recognition is one of the topics of artificial intelligence, computer vision, image processing, and machine vision. The classical problem in these areas of computer science is that of determining object via characteristic features. An important feature of the object is its contour. Accurate reconstruction of contour points leads to possibility to compare the unknown object with models of specified objects. The key information about the object is the set of contour points which are treated as interpolation nodes. Classical interpolations (Lagrange or Newton polynomials) are useless for precise reconstruction of the contour. The chapter is dealing with proposed method of contour reconstruction via curves interpolation. First stage consists in computing the contour points of the object to be recognized. Then one can compare models of known objects, given by the sets of contour points, with coordinates of interpolated points of unknown object. Contour points reconstruction and curve interpolation are possible using a new method of Hurwitz-Radon matrices.