Content Based Image Retrieval Using Two Color Feature Extraction

Abstract

Content Based Image Retrieval (CBIR) is a process to search for an image based on the content or features that are inside. Nowadays, many image retrieval applications have been made to meet the needs, so this application can provide convenience in terms of the introduction and search for an image. In this research, we used 10 different objects as image retrieval consists of Bicycle, Cow, Flower, Frangipani, Grape, Horse, Lovebird, Orange, Strawberry, Tree. These objects can be expressed in 10 classes. Our aim using these objects is viewed from the color of every object and the object of a different kind. From that point of view we built a CBIR system by utilizing the main features of the object (image). The main feature is the color feature. In this research, the main process is the extraction of color features with the color histogram and color moments. So in this research it will produce feature extraction by measuring the similarity in the library image. This measurement is done by calculating the closest distance using the euclidean distance method. The data library used in this research is 10 pieces of data, the test data is 50 pieces with 5 pieces for each of these classes. After testing using data and methods described above, the results of accuracy are obtained that the application of the color moments method gets better results than the color histogram method.

Automatic Extraction of Color Features from Landscape Images Based on Image Processing

“…To simplify the adjustment of light effects, the different reflection coefficients can be decomposed as: Formula (15) shows that, when the ambient light intensity and light source intensity of a landscape image are fixed, the surface colors of plants/buildings on different levels are jointly determined by COS, COM, and COJ.…”

“…These studies are premised on the color features of landscape images. Therefore, the extraction of these features must be continuously explored and updated [10][11][12][13][14][15][16].…”

Aplikasi Penerjemah Sebagai Media Komunikasi Bagi Penyandang Disabilitas Menggunakan Kombinasi Metode Skin Detection-Anfis, KNN Dan TTS

“…Sedangkan metode kalsifikasi, K-NN adalah salah satu metode klasifikasi dengan mencari jarak terdekat antara data pembelajaran dengan objek data uji [16]. Perhitungan jarak dilakukan dengan mencari perhitungan kemiripan yang dihitung dengan euclidean distance [17]. Data uji didapatkan dari hasil tangkapan gambar dan telah di olah pada tahap segmentasi.…”

Evaluating the use of Instagram images color histograms and hashtags sets for automatic image annotation

“…An advance of color histograms is that are invariant to orientation and scale, and this feature makes it more powerful in image classification. Evidence to the above is the plethora of research studies using color histograms for image retrieval (Liu and Yang, 2013 ; Theodosiou, 2014 ; Mufarroha et al, 2020 ; Zhang et al, 2020 ).…”