This paper describes the development of an optical mark reader that can be used for counting the examination score from the multiple-choice answer sheet. The system is developed based on PC-type microcomputer connecting to an image scanner. The system operations can be distinguished into two modes: learning mode and operation mode. In the learning mode, the model corresponding to each type of answer sheet is constructed by extracting all significant horizontal and vertical lines in the blank-sheet image. Then, every possibly cross-line will be located to form rectangular area. In the operation mode, each sheet fed into the system has to be identified by matching the horizontal lines detected with every model. The data extraction from each area can be performed based on the horizontal and vertical projections of the histogram. For the answer checking purpose, the number of black pixels in each answer block is counted, and the difference of those numbers between the input and its corresponding model is used as decision criterion. Finally, the database containing a list of subjects, students, and scores can be created. The experimental results on many styles of answer sheets show the effectiveness of such a system.

The pathfinding analysis has importance for various working such as logistics, transportation, operation management, system analysis and design, project management, network and production line. Especially, game programming technology has effect to economic and dominates culture, increasingly. The shortest path analysis is artificial intelligent which developed capability about think cause and effect, learning and thinking like human. Heuristic technique is method for solving a problem which gets result or not. It may return unexpected value which depends on each problem. 3D game realtime strategy uses shortest path analysis control path for movement of character, wheeled vehicle, animals, and fantasy buildings. It uses path for movement ever time, both in sea, terra and sky (three layers). The position of 3D object use refers 2D coordinate. Generally, the most of 3D game strategy both on LAN and online will play on terrain more than inside building or the room. This research proposes two essences. It proposes comparison rapidity, intelligence and efficiency about seven path finding algorithms which is principle algorithm are familiar. These algorithms used in game computer extensively as follows [1] depth first search [2] iterative deepening [3] breadth first search [4] Dijkstra's algorithm [5] best first search [6] A-star algorithm (A*) [7] iterative deepening A*. Besides, this research proposes depth direction A* algorithm method which new method which use linear graph theory cooperate with A* algorithm calculate increase efficiency of avoid barrier object on maps and search for shortest path of multi-layer. It movement are natural characteristic more other method. The cost node grows less than A* algorithm in clear area and plan about expand node before processed. It guarantee about expand node less than A* algorithm node certainly. It takes time movement and avoid barrier object less than uses other algorithm. This work able decrease expand node 22.12-70.67% depend on property of area between pathway by define 3D rendering rate are stable.

Segmenting a liver and its peripherals from abdominal computed tomography is a crucial step toward computer aided diagnosis and therapeutic intervention. Despite the recent advances in computing methods, faithfully segmenting the liver has remained a challenging task, due to indefinite boundary, intensity inhomogeneity, and anatomical variations across subjects. In this paper, a semi-automatic segmentation method based on multivariable normal distribution of liver tissues and graph-cut sub-division is presented. Although it is not fully automated, the method minimally involves human interactions. Specifically, it consists of three main stages. Firstly, a subject specific probabilistic model was built from an interior patch, surrounding a seed point specified by the user. Secondly, an iterative assignment of pixel labels was applied to gradually update the probabilistic map of the tissues based on spatio-contextual information. Finally, the graph-cut model was optimized to extract the 3D liver from the image. During post-processing, overly segmented nodal regions due to fuzzy tissue separation were removed, maintaining its correct anatomy by using robust bottleneck detection with adjacent contour constraint. The proposed system was implemented and validated on the MICCAI SLIVER07 dataset. The experimental results were benchmarked against the state-of-the-art methods, based on major clinically relevant metrics. Both visual and numerical assessments reported herein indicated that the proposed system could improve the accuracy and reliability of asymptomatic liver segmentation.

Falls are significant public health problem. In the last few years, several researches based on computer vision system have been developed to detect a person who has fallen to the ground. This paper presents a novel fall detection technique namely the directional bounding box (DBB) to detect a falls event especially a situation of fall direction paralleling the line of camera's sight. The DBB is constructed with perspective side view transformation of depth information. Moreover, a new aspect ratio namely the center of gravity point (COG) is proposed to monitor human movement. The proposed technique was evaluated with the video data set gathering from a RGB-D sensor. The experimental result of the proposed technique was better both accuracy and response times than previous works.