Machine vision based teleoperation aid

When teleoperating a robot using video from a remote camera, it is difficult for the operator to gauge depth and orientation from a single view. In addition, there are situations where a camera mounted for viewing by the teleoperator during a teleoperation task may not be able to see the tool tip, or the viewing angle may not be intuitive (requiring extensive training to reduce the risk of incorrect or dangerous moves by the teleoperator). A machine vision based teleoperator aid is presented which uses the operator's camera view to compute an object's pose (position and orientation), and then overlays onto the operator's screen information on the object's current and desired positions. The operator can choose to display orientation and translation information as graphics and/or text. This aid provides easily assimilated depth and relative orientation information to the teleoperator. The camera may be mounted at any known orientation relative to the tool tip. A preliminary experiment with human operators was conducted and showed that task accuracies were significantly greater with than without this aid

The IPRS Image Processing and Pattern Recognition System.

IPRS is a freely available software system which consists of about 250 library functions in C, and a set of application programs. It is designed to run under UNIX and comes with full source code, system manual pages, and a comprehensive user's and programmer's guide. It is intended for use by researchers in human vision, pattern recognition, image processing, machine vision and machine learning

Meat color recognition using machine vision

New technologies are being developed to give an ease to the human in a variety of different field each and every day. Food industry is the key of development that led to the rise of human civilization. The development of food industry dealt with the husbandry of domesticated animal and plants creating food surpluses that enabled the development of more densely populated and stratified societies. The study of food is very important that improves the quality of human's life. When it comes to classify and grade a meat, the color of fresh meat is a sensory indicator of which affects the consumers behavior, especially the consistency of meat color and musculature. Other factors that influence consumers purchasing include security, nutrition and taste. There has been no report that grades the meat freshness in the process of meat delivery. Most of the meat freshness is grading manually by using the human eyesight at the meat's color and quantity of fats. A parameter to show the freshness of meat has only been analyzed manually using a human's eyes. This is some kind of difficult method when making a right decision whether the meat is fresh or not. In order to overcome this problem, meat grading method has been studied to show the mathematical calculation on the change of color hue, saturation, and intensity (HSI) values. This study focuses on grading system design that helps to characterize the meat freshness according to its color. Using a MATLAB Graphical User Interface (GUI) program, it can analyzes the color of the meat that being inspected. The theory of this program includes the calculation of the mean values and histograms, and the final result. This system is capable of classifying meat freshness

Development of Moire machine vision

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis

Knowledge-based vision and simple visual machines

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong