Inspection task is traditionally carried out by human. However, Automated Visual Inspection (AVI) has gradually become more popular than human inspection due to the advantageous in the aspect of high precision and short processing time. Therefore, this paper proposed a system which identifies the object’s position for industrial robot based on colors and shapes where, red, green, blue and circle, square, triangle are recognizable. The proposed system is capable to identify the object’s position in three modes, either based on color, shape or both color and shape of the desired objects. During the image processing, RGB color space is utilized by the proposed system while winner take all approach is used to classify the color of the object through the evaluation of the pixel’s intensity value of the R, G and B channel. Meanwhile, the shapes and position of the objects are determined based on the compactness and the centroid of the region respectively. Camera settings, such as brightness, contrast and exposure is another important factor which can affect the performance of the proposed system. Lastly, a Graphical User Interface was developed. The experimental result shows that the developed system is highly efficient when implemented in the selected database.

Robotic vision system has taken a great leap in the field of robotics. Vision system is an essential tool to be implemented in a robot for visual communication between robot and human especially in the application of Tele-Diagnostic Robot. The robot vision system must always be in the field of view. The ability for the vision system to automatically track the person in communication is crucial for the remote medical specialist. To circumvent this problem, a face detection technique is implemented and it is performed using skin color segmentation with two color space which are YCbCr and HSV. Besides that, morphological operations are also done to detect the face region accurately. Two DOF servo mechanism were designed to ensure that the servo motor rotates to centralize the detected face region. A real-time testing were conducted and it was found that this system results a good performance.