A machine vision system was developed to investigate the detection of watermelon seeds exterior quality. The main characteristics of watermelon seeds appearance including area, perimeter, roughness and minimum enclosing rectangle were calculated by image analysis. Least square support vector machine optimized by genetic algorithm was applied for the classification of watermelon seeds exterior quality, and the broken seeds, normal seeds and high-quality seeds were distinguished finally. The surface irregularities defects of watermelon seeds were detected by machine vision grid laser. The experimental results show that the watermelon seeds exterior quality could be well detected and classified by machine vision based on least squares support vector machine.
A material on-line identification system based on THz time-domain spectroscopy using VC was developed in this paper. The main functions including data reading, linear motor driving, the calculation of optical parameters, the display and management of curve, the management of interface, the analysis of historical data , the maintenance and updating of database, and on-line identification based on principal component analysis were realized. As the prototype of material detection application, the material whose corresponding type characteristic spectrum has already existed in the database could be well identified.
An intelligent home system controlled via GSM, GPRS and the Internet was developed to investigate the control system of intelligent home. The home environment including concentration of carbon dioxide, UV intensity, light intensity, smoke concentration, temperature and humidity were real-time transmitted to the host computer monitoring platform. The intelligent home system supports four different control methods with the remote control functions of household appliances, security locks of doors, lighting system and smart curtains realized through a variety of network.
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