Classification of tea grains based upon image texture feature analysis under different illumination conditions

Tea Category Identification Using a Novel Fractional Fourier Entropy and Jaya Algorithm

“…The tea-leaves are not reused We spread the tea-leaves thinly over the tray, and then employed a 3-CCD digital camera to acquire tea images. Compared to 1-CCD cameras, 3-CCD cameras provide high-resolution images with lower noise [23]. The lighting arrangements were classified as two types: front or back lighting [31].…”

“…Genetic neural-network (GNN) was used to build the identification system, which yielded promising effects of identification with eight parameters of color and shape. Laddi et al [23] suggested acquiring tea granule images using a 3-CCD camera in the illumination condition of dual ring light. Gill et al [24] overviewed various computer vision based algorithms for texture and color analysis with a special orientation towards monitoring and grading of made tea.…”

Identification of Green, Oolong and Black Teas in China via Wavelet Packet Entropy and Fuzzy Support Vector Machine

“…The appropriate wavelength ranges of light are directed to the corresponding CCDs. In general, a 3-CCD camera provides better image quality through enhanced resolution and lower noise [20] than a 1-CCD camera.…”

“…They predicted computer vision based techniques will become more and more popular in tea classification. Laddi et al [20] acquired the images of tea granules using 3-CCD color camera under dual ring light. In all, 10 graded tea samples were obtained and analyzed.…”

Identification of Fake Green Tea by Sensory Assessment and Electronic Tongue

“…Recently, there have been some methods about identification of geographical origin of tea and quality evaluation of tea, including near-infrared spectroscopy (He et al, 2012), chemical fingerprint spectrum (Wang et al, 2014;Deng and Yang, 2013), machine vision system (Gill et al, 2011;Laddi et al, 2013), electronic nose (Cheng et al, 2013) and electronic tongue (He et al, 2009). As a new analytical measures, electronic tongue based on electrochemical, photochemical and enzymatic sensor array is widely used in foodstuff studies of identification and quality control, such as analysis of characterization and age of wine (Peris and Escuder-Gilabert, 2013;Rudnitskaya et al, 2010), analysis of milk adulteration (Escuder-Gilabert and Peris, 2010) and mineral water (Sipos et al, 2012), analysis of taste of beer (Cetó et al, 2013), identification of geographical origins of cocoa beans (Teye et al, 2014), identification of tea grade (Banerjee et al, 2012).…”