Development of Fuzzy Logic Based Differentiation Algorithm and Fast Line-scan Imaging System for Chicken Inspection

Yang, Chun‐Chieh; Chao, Kaunglin; Chen, Y.-R.; Kim, M.S.; Chan, Diane E.

doi:10.1016/j.biosystemseng.2006.08.009

Cited by 14 publications

(13 citation statements)

References 12 publications

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“…Researchers have used these differences for developing an online imaging system for real-time detection of contaminated chickens (Yoon et al, 2011;Chao et al, 2014). Researchers have also developed imaging systems for contamination detection in chicken carcasses in an off-line mode Lawrence et al, 2004).On the basis of differences in the spectra of healthy and systemically diseased chicken, HIS was applied for identification of systemically diseased carcasses (Yang et al, 2006;Chao et al, 2007;Chao et al, 2008;Yang et al, 2010). HIS was also found to be useful for microbial spoilage detection (TVC) in chicken filets (Feng & Sun, 2012).…”

Section: Applications Of Hsi In Poultry Sectormentioning

confidence: 99%

“…The utility of the technique for cancer and other disease diagnosis has also been demonstrated on various animal models (Fei et al, 2012). Further, it has also been exploited for detection of tumours (Kim et al, 2004;Kong et al, 2004;Nakariyakul & Casasent, 2007) and systemic diseases (Yang et al, 2006;Yang et al, 2010)in chicken carcasses. Moreover, as HSI can differentiate between healthy and diseased tissues, the technique can be used as a monitoring tool during surgery for improving the chances of removal of all cancerous tissue by enhancing visualization of cancerous tissue during surgery (Panasyuk et al, 2007).…”

Section: Applications Of Hsi In Dairy Industrymentioning

confidence: 99%

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Hyperspectral imaging (hsi): applications in animal and dairy sector

Kumar¹,

Saxena²,

Shrivastava³

et al. 2016

JEBAS

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Hyperspectral imaging (HSI), also known as imaging spectroscopy or 3D spectroscopy, combines imaging and spectroscopy into a single system. With a high resolution measurement of spectral signatures, HSI is able to provide critical information of the target. Thus it is useful for various scientific and industrial applications, including food safety and disease diagnosis. Due to constantly increasing demands for safe animal products, there is pressure on the processing sector for applications of advanced, high throughput methods for non-destructive quality analysis of animal products. In this context, HSI finds its applications for grading, classification, quality & composition analysis of animal products including meat, egg, milk etc. Further, the technique is also a useful tool in poultry sector for assessment of wholesomeness and quality control of chicken carcasses, as well as, chicken meat products. In fish industry also, the technique has established its potential for determining freshness and quality attributes of sea-foods. Apart from quality control of animal products, HSI has also demonstrated its usefulness for disease diagnosis in animal models and for detection of mammary cancers in dogs. Thus, the future of HSI technology in animal industry is promising and associated with multivariate analysis, HSI technique will further dominate in animal products authentication and analysis in the future also.

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Section: Applications Of Hsi In Poultry Sectormentioning

confidence: 99%

Section: Applications Of Hsi In Dairy Industrymentioning

confidence: 99%

Hyperspectral imaging (hsi): applications in animal and dairy sector

Kumar¹,

Saxena²,

Shrivastava³

et al. 2016

JEBAS

View full text Add to dashboard Cite

show abstract

“…This has been demonstrated in recent years in the development of a reflectance-based imaging system for inspection of chicken carcass wholesomeness on high-speed processing line operations [6,7]. In addition, the application of hyperspectral/multispectral line-scan imaging has been further extended in the realm of fluorescence methods for online apple inspection [3].…”

Section: Introductionmentioning

confidence: 99%

Multispectral line-scan imaging system for simultaneous fluorescence and reflectance measurements of apples: multitask apple inspection system

Kim

Lee

Chao

et al. 2008

Sens. & Instrumen. Food Qual.

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In this methodology paper, a recently developed line-scan imaging system, capable of simultaneously acquiring a combination of multispectral reflectance and fluorescence from rapidly moving objects, is presented. The system can potentially provide multitask inspections for quality and safety attributes of apples due to its dynamic selectivity in multispectral bands, each with independent spectral bandwidth in the fluorescence and reflectance domains. Mounted on a commercial applesorting machine, the system was evaluated to determine the image pixel (spatial) resolution for apples at a sorting line speed of three to four apples per second. Apples loaded on the sorting machine were spaced approximately 15 cm apart. With these parameters, the resulting images showed approximately 40 line-scan images per apple, for a horizontal spatial resolution of 2 mm per pixel. In the vertical direction, with 1,002 pixels available for each line-scan image, the spatial resolution of the system can be as high as approximately 0.2 mm per pixel depending on the choice of binning. The combined spatial resolution is comparable to that in our previous studies and is adequate for imagebased online inspection of defects and fecal contamination on apples.

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“…There have been several research studies using multispectral imaging systems for chicken carcass inspection [3,4]. Multispectral images contain spectral and spatial information from the surface of chicken carcasses, which both studies identified as being essential for efficient identification of contamination and systemic disease.…”

Section: Introductionmentioning

confidence: 99%

“…Multispectral images contain spectral and spatial information from the surface of chicken carcasses, which both studies identified as being essential for efficient identification of contamination and systemic disease. Many studies [3][4][5] have shown that the proper selection of wavelengths is essential for successful multispectral imaging applications. Once specific wavelengths and image features that can increase classification accuracy for chicken inspection have been determined using data from a hyperspectral imaging system, it is usually necessary to implement them into a separate multispectral imaging system in order to achieve fast imaging for online inspection applications.…”

Section: Introductionmentioning

confidence: 99%

Machine vision system for online inspection of freshly slaughtered chickens

Yang

Chao

Kim

2008

Sens. & Instrumen. Food Qual.

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A machine vision system was developed and evaluated for the automation of online inspection to differentiate freshly slaughtered wholesome chickens from systemically diseased chickens. The system consisted of an electron-multiplying charge-coupled-device (EMCCD) camera used with an imaging spectrograph and controlled by a computer to obtain line-scan images quickly on a chicken processing line of a commercial poultry plant. The system scanned chicken carcasses on an eviscerating line operating at a speed of 140 chickens per minute. An algorithm was implemented in the system to automatically recognize individual carcasses entering and exiting the field of view, to locate the region of interest (ROI) of each chicken, to extract useful spectra from the ROI as inputs to the differentiation method, and to determine the condition for each carcass as being wholesome or systemically diseased. The system can acquire either hyperspectral or multispectral images without any cross-system calibration. The essential spectral features were selected from hyperspectral images of chicken samples. The differentiation of chickens on the processing line was then carried out using multispectral imaging. The high accuracy obtained from the evaluation results showed that the machine vision system can be applied successfully to automatic online inspection for chicken processing.

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Development of Fuzzy Logic Based Differentiation Algorithm and Fast Line-scan Imaging System for Chicken Inspection

Cited by 14 publications

References 12 publications

Hyperspectral imaging (hsi): applications in animal and dairy sector

Hyperspectral imaging (hsi): applications in animal and dairy sector

Multispectral line-scan imaging system for simultaneous fluorescence and reflectance measurements of apples: multitask apple inspection system

Machine vision system for online inspection of freshly slaughtered chickens

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