Simulation of chromatic and achromatic assessments for camouflage textiles and combat background

Author(s):  
Md Anowar Hossain

Chromatic and achromatic (AC) assessments of camouflage textiles have been critical to the defense researchers for concealment, detection, recognition, and identification (CDRI) of target signature against multidimensional combat background (CB). AC assessment and camouflage measurement techniques are simulated and experimented for assessment of camouflage textiles against CB. This model has been demonstrated for color measurement spectrophotometer, scanning electron microscopy (SEM), digital imaging, hyperspectral imaging, and image processing software (ImageJ) for the advancement and establishment of AC camouflage textiles assessment. The chromatic variations of 48 artificial target objects (TOBs) have been synthesized by image processing; the technique can be implemented for defense CB-CDRI assessment. Microstructural variation versus optical signal of woodland, desertland and stoneland CB materials have been elucidated by SEM magnification. The achromatic variation of CB materials have been demonstrated for the replacement of optical signal against modern remote sensing device to the imaging sensor. Color difference (Δ E), microstructural variations, pixel variations to imaging signal and standard deviation of CB materials have been represented for remote sensing surveillance of defense applications against TOB-CB-CDRI. Technical simulation of color, texture, gloss, and pixel intensity has been derived for AC-CDRI assessment of camouflage textiles in TOBs-CB environment.

Author(s):  
H. Zhang ◽  
D. Zhao ◽  
F. Xie ◽  
Z. Jiang

Abstract. Remote sensing is not only the teaching content of the majors of surveying and mapping, but also the teaching content of many other engineering majors in China, such as Detection, Guidance and Control Technology (DGCT), Aerocraft Control and Information Engineering (ACIE), etc. In this paper, we put forward the special teaching task of remote sensing image processing software design to the practical courses, named Specialty Course Design and Specialty Comprehensive Experiments, for senior engineering undergraduate students in their last academic year. In this research oriented task, students are required to design, code and implement a remote sensing image processing software under the specified software programming conditions, and carry out detailed software testing, so as to meet several application functions with research objectives. According to the collation and summary of five rounds of teaching practice of such research oriented remote sensing image processing software design tasks in practical courses, we find that it can not only cultivate the ability of students to comprehensively use the knowledge they have learned, but also enable them to better analyze the actual application needs and acquire the technology and ability closer to the actual work needs.


2020 ◽  
Vol 40 (1) ◽  
pp. 21
Author(s):  
Ferlando Jubelito Simanungkalit ◽  
Rosnawyta Simanjuntak

Color had a correlation with physical appearance, nutritional and chemical content as well as sensory properties which determine the quality of agricultural products and foods. Conventional color measurements were performed destructively using laboratory equipment. Therefore, color measurement methods of agricultural products were needed more quickly, accurately and non-destructively. This study aimed to develop a Computer Vision System (CVS) that can be used as a tool to measure the color of fruits. The designed CVS consists of a 60x60x60 cm black mini photo studio; a pair 15 watt LED lighting, sony α6000 digital camera, a set of laptop and an image processing software applications. Image processing software was programmed using VB.Net 2008 programming language. The developed CVS was calibrated using 24 color charts Macbeth Colorchecker (Gretag-Macbeth, USA). The calibration results of 24 color chart of Macbeth Colorchecker was resulted in a MAPE (Mean Absolute Percentage Error) value of component R / Red = 0%; G / Green = 0% and B / Blue = 0,5%; with 99% accuracy rate. In color measurement, the developed CVS had a 95% accuracy rate.


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