FISHEYE IMAGING APPROACH WITH THE SUPERVISED MACHINE LEARNING FOR THE DETERMINATION OF FRESHNESS OF FISH

CARLAK H. F., Kandemir K., ÜNLÜSAYIN M.

FRESENIUS ENVIRONMENTAL BULLETIN, cilt.30, sa.9, ss.10754-10762, 2021 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 30 Sayı: 9
  • Basım Tarihi: 2021
  • Dergi Adı: FRESENIUS ENVIRONMENTAL BULLETIN
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Chemical Abstracts Core, Communication Abstracts, Environment Index, Geobase, Greenfile, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.10754-10762
  • Anahtar Kelimeler: Fish freshness, image processing, local binary pattern, wavelet transform, machine learning, COLOR
  • Akdeniz Üniversitesi Adresli: Evet

Özet

One of the most important selective specification in determining the quality, of fish is its freshness. In this study, the fast and sensitive alternative technique is proposed as the fish freshness detection. 120 different images of 20 red mullet fish images were taken with an interval of 8 hours in two days. The segmentation of fisheyes according to a fully automatic computerized vision was acquired from the digital images of fish samples. Three different methods have been proposed to identify- the fish freshness after the segmentation process. The first method is the local binary- pattern (LBP) method. The distance between histograms obtained by this method was examined and compared with Chi -Square Divergence, Kullback-Leibler Divergence, and Correlation methods. Next, the discrete wavelet transform was performed. The energy densities of these wavelet transforms were investigated. The data obtained from these methods provide a strategic framework for the assessment of fish freshness. Then, the histograms obtained from the LBP method were educated with supervised machine learning. As a result of the tests, the freshness situation of 18 fish was determined within 20 red mullet fish.