title: Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates part 2: realization of rapid blood stain detection.
abstract: Based on the blood stain detection method and criteria established in part 1 of this article, we combine and organize all necessary tasks to realize the multispectral imaging-based rapid blood stain detection system. To rapidly detect blood stains on the test surface, the developed system automatically captures the spectral images, extracts their spectral data, determines the positions of blood stains, and accurately highlights the positions of blood stains on the display. To achieve such a system, several tasks are newly introduced, including adjustment of camera exposure times to prevent image saturation or excessive darkness, the search for the sampled clean positions of the substrate to determine the substrate reflectance spectrum, and suitable detection procedures and proper arrangement of criteria to eliminate unnecessary calculations. Parallel processes between image capturing and blood stain identification help shorten the time for blood stain identifications despite a large amount of spectral data to be processed. The developed system can identify blood against several other reddish brown stains on several substrates. The measured average identification times on different test surfaces range from only 23.3 to 28.7 s, including the image capturing process.
authors.affiliation: Physics Department, Faculty of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
authors.forename: Suwatwong
authors.initials: S
authors.lastname: Janchaysang
authors.forename: Sarun
authors.initials: S
authors.lastname: Sumriddetchkajorn
authors.forename: Prathan
authors.initials: P
authors.lastname: Buranasiri
mesh_terms: D000465:Algorithms; D001331:Automation; D001769:Blood; D001801:Blood Stains; D002138:Calibration; D003116:Color; D005554:Forensic Medicine / Q000295:instrumentation* / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D013057:Spectrum Analysis / Q000295:instrumentation / Q000379:methods; D013997:Time Factors