There has been extensive use of daily otolith growth increments in age and growth ·studies of age-O fishes (Campana and Neilson 1985). Recently, the daily ageing method has been extended to scales (Szedlmayer et al. In press). However, visually counting increments is tedious, time consuming, and subject to human error (Rice 1987). In an effort to automate the counting of increments or daily circuli in scales of age-O juvenile weakfish Cynoscion regalis, a microcomputer-based system was used to digitize the video image of a scale, store the light intensities from a radial transect, and count circuli

Sieracki, Michael E.

Szedlmayer, Margaret M.

Szedlmayer, Stephen T.

English

College of William & Mary: W&M Publish

W&M ScholarWorks VIMS Articles Virginia Institute of Marine Science 1990 Automated enumeration by computer digitization of age-0 weakfish Cynoscion regalis scale circuli Stephen T. Szedlmayer Margaret M. Szedlmayer Michael E. Sieracki Virginia Institute of Marine Science Follow this and additional works at: https://scholarworks.wm.edu/vimsarticles  Part of the Marine Biology Commons Recommended Citation Szedlmayer, Stephen T.; Szedlmayer, Margaret M.; and Sieracki, Michael E., Automated enumeration by computer digitization of age-0 weakfish Cynoscion regalis scale circuli (1990). Fishery Bulletin, 89, 337-340. https://scholarworks.wm.edu/vimsarticles/2192 This Article is brought to you for free and open access by the Virginia Institute of Marine Science at W&M ScholarWorks. It has been accepted for inclusion in VIMS Articles by an authorized administrator of W&M ScholarWorks. For more information, please contact scholarworks@wm.edu. Michael E. SierackiVirginia Institute of Marine Science.College of William and Mary. Gloucester Point. Virginia 23062Stephen T. SzedlmayerMargaret M. SzedlmayerAuburn University. Marine Extension and Research Center4170 Commanders Drive. Mobile. Alabama 36615Automated Enumeration by ComputerDigitization of Age-O WeakfishCynoscion regalis Scale Circuli *There has been extensive use ofdaily otolith growth increments inage and growth ·studies of age-Ofishes (Campana and Neilson 1985).Recently, the daily ageing methodhas been extended to scales (Szedl-mayer et al. In press). However,visually counting increments is tedi-ous, time consuming, and subject tohuman error (Rice 1987). In an ef-fort to automate the counting of in-crements or daily circuli in scales ofage-O juvenile weakfish Cynoscionregalis, a microcomputer-based sys-tem was used to digitize the videoimage of a scale, store the lightintensities from a radial transect,and count circuli. Circuli were alsocounted visually to verify the accu-racy of the software. Others haveused microcomputer-based systemsto aid in increment counting (Tzengand Yu 1988, Thorrold and Williams1989, Karakiri et al. 1989), but toour knowledge the present algo-rithm is the first method that com-pletely automates increment coun-ting with a high degree of accuracy.Materials and methodsAge-O juvenile weakfish were col-lected from the York River, Virgi-nia (for further collection methods,• Contribution no. 1632 of the Virginia Insti-tute of Marine Science, College of Williamand Mary.see Szedlmayer et aI. 1990). Fish,50-140mm standard length (n =45), were anesthetized with tricanemethanol sulfate (50 mg MS-222/Lseawater), and scales removed fromjust below the midbody lateral linecurve. The scales were placed on aglass slide in water and cleanedwith a paint brush, then permanent-ly mounted with a methacrylatecopolymer, and covered with a glasscover slip (Flo-Texx liquid coverslip, Lerner Lab.).For the visual method, scale cir-culi were counted twice by the samereader, along a central radius fromthe focus to the edge, on the anter-ior side, at 125 x magnification onan Olympus BH-2 microscope. Ifcounts were not the same, theywere counted a third time. Only 1out of 45 required a third count, andfor that scale the counts that werethe same were used for comparisonwith automated computer counts.For automated counting, scaleswere digitized using the same mag-nification and radius as visual counts.Scale images were detected by aIkigami ITC-510 video camera (625-line resolution) mounted on themicroscope, digitized by a MatroxPIP-512B image analyzer, and storedin computer memory in a matrix of512 x 512 picture elements (pixels)with 256 gray levels for each pixel.A PC-AT 286 computer with a 10-meg Hz processor, I-meg RAM, andmath coprocessor controlled theimage analyzer. A 40-megabyte harddisk and a floppy disk drive wereused for image and data storage.Once the image was digitized, itwas displayed on a Panasonic PM205A video monitor (lOOO-line reso-lution) and a mouse wasused to con-trol the movement of a cursor markprojected on the image. The cursorwas then positioned to select twopoints defining a transect from thefocus to the edge of the scale per-pendicular to the circuli (Fig. 1).Light intensities (gray levels) ofthree transects, each one pixelapart and one pixel wide, weresimultaneously stored to the harddisk. Each transect was then ana-lyzed using a Fortran program toidentify and count scale circuli. Thealgorithm applied a moving average(7,8,9, and 10 pixel averages weretried) to smooth each transect andthen searched for local minima (e.g.,10 pixels on either side of the inflec-tion point corresponds to a localminimum within a search width of20 pixels; search widths of 18, 20,22, and 24 pixels were tried). TheFortran counting algorithm com-pared adjacent pixels and deter-mined if light intensity increased ordecreased. Subsequently, an incre-ment was counted only after thefollowing two criteria were satis-fied: (1) an inflection point wasdetected, i.e., a change in light in-tensity from decreasing to increas-ing and (2) the inflection point wasthe'minimum light intensity withinthe specified search width. Depend-ing on the scale size, one to five im-ages were needed to complete ascale count (i.e., with smaller scalesthe complete scale was included inthe digitized image, but with largerscales several images were neededat the same magnification to includeall circuli from the focus to theedge). The computer counts (aver-Manuscript accepted 14 November 1990.Fishery Bulletin, U.S. 89:337-340 (1991).337338 Fishery Bulletin 89(2). 1991Results and discussionages of the three counts from individual scales) werethen regressed against the visual counts.Application of a nine-pixel smoothing interval on thetransect data combined with a 20-pixellocal-minimasearch width, produced the highest coefficient of deter-mination (r 2 0.99) between the automated and visualcounts (Fig. 2). Other combinations of smoothing in-terval and 'search width resulted in lower coefficients.The present program allows adjustment of smoothinginterval and search width to optimize its use with otherfish species. Computer counting was approximately 3.3times faster than visual counting. The visual methodshowed a slightly higher precision compared with com-puter counting, but savings in time more than compen-sates for this small increase in error (Table 1). In addi-tion, the concentration needed and subsequent fatiguein visual counting compared with computer countingare difficult to measure, yet computer counting wasconsidered much easier by all scale readers.Microcomputer systems that can digitize incrementsfrom scales, otoliths, and other bony structures havebeen previously reported and demonstratedpotential for automated counting (McGowan etal. 1987). The present system makes an ad-vance over other systems by using the local-minimum method of increment identification.Previous methods usually use threshold-lightintensity levels to identify increments thatmay produce discrepancies between computerComputer countsVisual countsTable 1Comparison of counts and counting times of scale circuli from weakfishCynoscion 'regalis between computer and visual methods from a ran-dom subsample of those counted. Each scale was from a different fish.Figure 1Photograph of a weakfish scale with 29 circuli (29 circuli +edge = count of 30). Arrow depicts counting transect fromfocus to perimeter along the anterior growing side (transectline = 0.5mm).Time TimeScale 1st 2d 3d (s) 1st 2d 3d it (s)1 36 36 46 38 38 38 38.0 132 32 32 42 31 31 32 31.3 163 32 32 41 31 32 33 32.0 134 37 37 46 39 38 38 38.3 125 32 32 42 31 31 32 31.3 166 30 30 39 30 30 30 30.0 127 50 51 50 106 51 52 50 51.0 138 60 60 82 64 62 61 62.3 359 46 46 51 48 47 49 48.0 1910 43 43 45 44 44 44 44.0 1511 58 58 94 60 60 60 60.0 2612 64 64 74 66 67 65 66.0 2513 60 60 80 61 58 61 60.0 3114 49 49 56 50 50 50 50.0 1515 58 58 69 60 58 58 58.7 14x60.9 x18.3SD21.7 SD 7.4Paired t-statistic = 8.85, t critical value Oevel = 0.05) = 2.145, thereforethere is a significant difference between counting time.70.'30 40 50 60 70Visual countFigure 2Linear regression of computer automated count onvisual count of scale circuli from weakfish, Cynos-cion regalis (N 45 fish, r 2 0.99, y = 1.03x - 0.3).NOTE SZed/mayer et a/.: Automated enumeration of age-o Cynoscion rega/is scale circuli 3391208040Figure 3Light intensities along a transecttaken from a single scale by distancein mm. (A) Light intensities of asingle transect. (B) Smoothed datausing a nine-point moving average.Dashed line represents a thresholdlight intensity of 90. Lowering thethreshold to include peak Y wouldeliminate peaks under Z.120100f-80mm0.016 0.023b cAFigure 4Light intensities from a section of a scaletransect enlarged to illustrate pixel spacing.Circuli spacing changed. but each minima (a,b, and c) were only counted once. Inflectionpoint (d) was detected but not counted as a cir-culus, because it was not a local minimum ina 20-pixel search width. Horizontal lines aboveletters represent search width size = 20 pixels.rnc~1::1~ _~~Bo 0.2 0.4Transect Distance mm20 40 60Pixels80 100and visual counts, because background intensity levelschange as the transect moves across the otolith or scale.Thus, some areas may be counted incorrectly whenthey fall below the selected threshold level as shownfor a transect across a weakfish scale (Fig. 3). The local-minimum method solves this problem, since identifica-tion of increments is only dependent on adjacent pixel-light intensity levels. The local-minimum method alsoresponds to changes in increment spacing: as incrementspacing increases (measurements from one typical scaleranged from 10.3 to 22.9m- 6) the algorithm movesgreater distances (more pixels) along the transect, butdoes not count more increments until another minimumis detected. For example, in Figure 4, increments a,b, and c were each counted as one circulus despitechanges in circuli spacing, but inflection point d wasnot counted because it was not a local minimum withina 20-pixel search width.Increments narrower than the selected search widthwould cause errors (e.g., microincrement spacing width= 10 pixels, but search width = 20 pixels). However,this problem can be corrected in three ways: (1) reducethe search width; (2) increase the magnification of thescale or otolith, e.g., from 125 to 400; or (3) increasethe number of pixels between increments, i.e., increasethe resolution of your system as discussed below. Inaddition, the true limit of counting narrow incrementsis not the algorithm, but the resolution limit of the lightmicroscope. After projection of the image onto thevideo monitor, one pixel corresponds to an actual dis-tance of about 0.2m- 6 (with the light microscope at1000x). This 0.2m- 6 size is the maximum theoreticalresolution of any light microscope (Eastman Kodak Co.1980). In addition, " ... the functional limits are in-variably higher than those derived theoretically" (Cam-pana et al. 1987), therefore several pixels may be pre-sent even between the smallest detectable increments.Other advantages of the present system, as well asother systems, include elimination of data entry andassociated transcriptional errors, and establishment ofrepeatable criteria for ageing of fishes.A disadvantage of the present system and othersimilar systems is that clearly defined increments areneeded. This was not a problem with weakfish scalesbecause circuli are distinct (Fig. 1), but application tootolith increments may need further refinement.Another disadvantage is that most systems need multi-ple images to complete a transect reading of a singlescale or otolith, which may increase processing timeand errors. The multiple-image-per-transect problemresults from a limiting number of pixels (512 x 512pixels) in our digitizer, such that lower magnifications(25 or 40) that would encompass the entire transect donot contain enough pixels for accurate identificationof increments. Systems with greater pixel resolution(e.g., 1024 x 1024) would alleviate this problem, and arenow commercially available.340AcknowledgmentsWe wish to thank Steve Reichenbach and Charlie Vilesfor their help in programing the digitizer, Karen Ripplefor help in counting scale circuli, and Kenneth W. Ablefor review of the manuscript.CitationsCampana, S.E., and J.D. Neilson1985 Microstructure of fish otoliths. Can. J. Fish. Aquat. Sci.42:1014-1032.Campana, S.E., J.A. Gagn', and J. Munro1987 Otolith microstructure of larval herring (Clupeaharengus): Image or reality. Can. J. Fish. Aquat. Sci. 44:1922-1929.Eastman Kodak Co.1980 Photography through the microscope. Eastman KodakCo., Rochester, NY, 96 p.Karakiri, M., R. Berghahn, and H. von Westernhagen1989 Growth differences in O-group plaice PleurortR-ctes platessa.as revealed by otolith microstructure analysis. Mar. Ecol.Prog. Ser. 55:15-22.McGowan. M.F., E.D. Prince. and D.W. Lee1987 An inexpensive microcomputer based system for mak-ing rapid and precise counts and measurements of zonatiqnsin video displayed skeletal structures of fish. In Summerfelt,R.C., and G.E. Hall (eds.), The age and growth of fish, p.385-395. Iowa State Univ. Press, Ames.Rice, J.A.1987 Reliability of age and growth-rate estimates derived fromotolith analysis. In Summerfelt, R.C., and G.E. Hall (eds.),The age and growth of fish, p. 167-176. Iowa State Univ.Press, Ames.Szedlmayer. S.T.. M.P. Weinstein, and J.A. Musick1990 Differential growth among cohorts of age-O weakfishCynoscion regalis in Chesapeake Bay. Fish. Bull.. U.S. 88:745-752.Szedlmayer, S.T., K.W. Able. J.A. Musick, and M.P. WeinsteinIn press Are scale circuli deposited daily in juvenile weakfish,CynoscWn 1-egalis? Environ. Bioi. Fish.Thorrold, S.R., and D. McB. Williams1989 Analysis of otolith microstructure to determine growthhistories in larval cohorts of a tropical herring (Herklotsickthyscastelnaui). Can. J. Fish. Aquat. Sci. 46:1615-1624.Tzeng, W.-N., and S.-Y. Yu1988 Daily growth increments in otoliths of milkfish, Chanoschanos (Forsskal), larvae. J. Fish. BioI. 32:495-504.Fishery Bulletin 89(2). 1991

Automated enumeration by computer digitization of age-0 weakfish Cynoscion regalis scale circuli

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Automated enumeration by computer digitization of age-0 weakfish Cynoscion regalis scale circuli

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