Iman H. Kartowisastro

Local Positioning System of a Mobile Robot : A Practical Perspective

Localization problem in determining position and orientation of an autonomous robot with respect to a world reference frame is commonly encountered. Personal service robot which has the largest share in the growth of service robot needs a simple and affordable system to overcome this problem. This paper presents an alternative approach to solve localization problem by utilizing local positioning system based on ultrasonic sensors. With this system, 3D information in regards to position and information of a mobile robot can be obtained fast enough to cope with a robot moving with a speed of 30 cm/s. The use of LPS to enhance the performance of control system has been already proven for a mobile robot moving on area with high irregularity surface

Diminishing Variant Illumination Factor in Object Recognition

Undetected object(s) from a camera due to a poor condition of light intensity, or shadow that appears are problems that can occurs in object detection. This can lead to a loss, especially when applied in the industrial world. The purpose of this research is to fix an illumination factor, particularly the shadow factor on an image that will be detected by combining two methods, namely adaptive single scale retinex and shadow removal. Smoothing from retinex and shadow removal process are performed after an image is captured. Accuracy of object detection obtained is 95.45%, using experimental image detection program and random sampling method from 22 images of two datasets used in this study. Namely “Shadow Removal Online Dataset and Benchmark for Variable Scene Categories” and “Klik BCA” which obtained from the simulation process. This method can be applied to real time conditions, where the speed of the process is stable and fast enough such that it can be applied into industrial companies to help their quality control.

Object Segmentation under Varying Illumination Effects

Image segmentation is one of the medium levels of image processing. In this paper, illumination is the issue of segmenting various objects. This work proposed and evaluated two methods for image segmentation. First, we proposed region growing based method to find region that represented object of interest. Second, we proposed edge suppressing based method by the use of analyzing tensor. The experiment demonstrated that region growing method has limitation in image segmentation for object color variation. The system shows effectiveness of the method by implementing edge suppressing method in three different objects as foreground object, and four different objects as background object. Using edge suppressing, this system performed successfully under different illumination intensities.