Content Based Image Retrieval using Feature Extraction Technique
Nandkumar S. Admile1, Jagadish Hallur2, Anup S.Vibhute3, Akshay A.Jadhav4, Vijay S.Bhong5
1Nandkumar Sushen Admile, Department of E&TC Engg.College of Engineering, Pandharpur.
2Jagdish S.Hallur, Department of E&TC Engg.College of Engineering, Pandharpur.
3Dr.Anup S.Vibhute, Department of E&TC Engg.College of Engineering, Pandharpur.
4Akshay A.Jadhav, Department of E&TC Engg.College of Engineering, Pandharpur.
5Vijay S.Bhong, Department of E&TC Engg. College of Engineering, Pandharpur.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 2527-2532 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3811129219/2019©BEIESP | DOI: 10.35940/ijeat.B3811.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Now days the image processing can be used in various areas such as in Agriculture, in Health care system also for security purpose. In case of Crime investigation the image processing can be used to identify the particular suspect from an available dataset for that purpose an image retrieval technique is presented in this paper. For image retrieval number of techniques is available. In earlier days Block Truncation Coding is used but due its some disadvantage feature extraction method is used. Using DDBTC technique two features are derived. The first feature as Color Co-occurrence Features (CCF) obtained using color quantizes features such as Bit Pattern Feature (BPF) is derived from Bitmap image. The five different distance metrics are used to measure the similarity between two images. The simulated results shows proposed Technique can shows the better result in the form of Average Precision rate (APR) and Average Recall Rate (ARR) as compared to other techniques.
Keywords: Average Recall Rate Average Precision Rate, Bit pattern feature, color co-occurrence feature, Dot diffused block truncation coding.