Al-Rafidain Engineering Journal (AREJ)

Image Fusion is applied to get back a group of data from two or more than two images and put it into one image to create additional wealthy information and profitable more than any of the input data that led to increase the features and performance of information.  The quality of the resultant data relies on the implementation of the process. Image fusion is excessively utilized in stereo camera fusion, medical application, manufacture process monitoring, electronic circuit design and inspection, complex machine diagnostics and in intelligent robots on assembly lines. This study displays a literature review on different types of algorithm and theories which apply on images. Many quality criteria have debated to do a brief comparison of these methods. The applications of image fusion are showed in this paper.

Nowadays, the mobile robot can be seen in different fields of engineering and science. The mobile robot can do some tasks that are so difficult or very risky to be performed by a human. Most of the works currently focus on implementing artificially intelligent algorithms and other algorithms that depend on the behaviour of nature. These approaches have been used in mobile robot navigation along uncertain manner. Mobile robot navigation strategies can be divided into two approaches: the classical approach and reactive approach. The classical approach related to static environment, whiles the reactive navigation is based on an unstructured environment. Path planning is one of the most important parts of the navigation system. In this paper, review and assessment of path planning strategies that can concern with the reactive approach are discussed, because it deal with the problem of dynamic environment.  Numerous reactive methods have been introduced. Most of these presented works were concerned with simulation and a few of them have shown experimental implementation. Many papers tried to make a combination between two algorithms or more to increase the efficiency. It is concluded that reactive algorithms need more learning phases, complex in design, and require large memory storage.

The human signature is an important biometric feature that is used to identify human identity. It is essential in preventing falsification of documents in numerous financial, legal, and other commercial settings. The computerized system enters many aspects of our life, security is one of them, continues developing in computer vision and artificial network leads researcher to develop computerized signature recognition. This paper proposed a real-time algorithm for signature recognition. It is based on client and server operation.in which, client agent captures a signature and sends it to the server through the network. The server receives data and performs processing on it. Processing algorithm is based on weightless neural network. It is chosen for its simplicity and few numbers of sample required for training. The algorithm is tested and evaluated and show the ability to process 4.7 images per second.

Any robot system consists of mechanical and electrical components. . Mostly and with time obsolescence, faults and errors are happen in robot systems lead to work problems. Many years ago, scientist and researchers are working in this field. In this paper, a review study focuses on this field is introduced to make classifications between different types of faults and diagnosis methods those used in the field of robotics. Many types of faults are studied, according to some previous and recent works. The most detected faults can be classified into two parts: hardware and software faults. The hardware faults part is further classified into two main types; the first one is represented in sensors and actuators, while the other is included taking into consideration both position and velocity in joints. These joints which usually connect the links of the arm with each other and ensure contentions to motors, controllers, and many sensors, are really represent the most important side have to be studied. The software faults part includes those errors occurred during programming such as any error happen in signal translation, signal classification or signal identification is considered as a software fault.