Colonizer: Anandroid OS based automated microbial colony counter

Abstract

Abstract:Colony counting to estimate colony forming units (CFUs) is a standard microbiology procedure used for determining the number of viable microbes in a system. Typically this process is done manually, which is time consuming, tedious, and sometimes error prone. Alternate image analysis based systems are also time consuming. In this paper we develop and demonstrate a simpleandroid based automated colony counter, called Colonizer, also made freely available on Google Playstore. Our algorithm can also threshold and segment overlapping colonies and thus provide rapid, accurate counts across a wide range of colony densities (from 50-500 colonies/plate), for different microbes, using any android based phone or device.Introduction:

A sensor-centric survey on the development of smartphone measurement and sensing systems

“…The system, featuring a spectral resolution of 0.305 nm/pixel, has been tested to measure pH for river quality water assessment [69] and to measure the concentration of BSA protein and trypsin enzyme [70]. [81], Poladia et al [82] and Kumar et al [83]. Other computer vision applications for smartphone include a system for continous surveillance of fruit flies [84], a food recognition tool assisted by image retrieval [85] and nutritional value estimation [86], a heart rate measurement system exploiting the time variation of acquired images of the user fingertip placed on the phone camera [87].…”

“…Despite the increasing interest in smartphone based sensing systems, there are also some gaps that from [190]. colorimetric alcohol concentration in saliva 0 -0.3% [38] colorimetric pH, protein and glucose in urine 5 -9, 0 -100 mg/dL, 0 -300 mg/dL [39] colorimetric blood hematocrit level 10 -65% [41] colorimetric streptomycin concentration in food 50 -267 nM [42] colorimetric BSA, catalase enzyme and carbohydrate 0 -1 mg/mL, 0 -1 mg/mL, 0 -140 µg/mL [43] colorimetric cloud coverage 4 -98% [48] colorimetric surface corrosion of iron N/A [50] irradiance measurement UVA solar irradiance 0 -10 mW/m 2 [60] irradiance measurement UVA aerosol optical depth 0.05 -0.20 [61] irradiance measurement UVB solar irradiance 1 -9 mW/m 2 [63] irradiance measurement atmospheric total ozone column 260 -320 DU [65] irradiance measurement SO 2 volcanic emission 0 -3. computer vision bacterial colony counter N/A [80] computer vision bacterial colony counter 0 -250 CFU [81] computer vision bacterial colony counter N/A [82] computer vision bacterial colony counter 0 -500 CFU [83] computer vision surveillance of fruit flies N/A [84] computer vision food recognition tool N/A [85] computer vision food recognition and nutritional value N/A [86] computer vision heart rate measurement N/A [87] mobile microscopy cell imaging (brightfield and fluorescent) N/A [88] mobile microscopy image analysis of green algae in freshwater N/A [89] sound recording and analysis chronic lung diseases average error 5.1%, detection rate 80 -90% [90] sound recording and analysis chronic lung diseases average error 8.01% [91] sound recording and analysis number of coughs detection rate 92% [92] sound recording and analysis respiratory rate estimation error < 1% [93] sound recording and analysis nasal symptoms N/A [94] sound recording and analysis snoring quantification correlation > 0.9 [95] sound recording and analysis hearing threshold in noisy environment N/A …”

TAMMiCol: Tool for analysis of the morphology of microbial colonies

“…The production of binary images has been used to quantify images by examining the selected pixels in binary images produced using a range of thresholds [22]. Software for counting bacterial colonies using Otsu’s method has been developed for mobile phones [33, Colonizer].…”