A Systematic Literature Review on Batik Image Retrieval

Batik is a traditional textile art form originating in Indonesia. The diversity of batik motifs results from the acculturation process, leading to different styles and variations in other regions. However, this diversity also poses a problem for society regarding identifying, classifying, and locating batik based on the motifs and areas. To address this issue, researchers have been using the Content-Based Image Retrieval (CBIR) approach, a study field that has been around for a while and is known for its real-time retrieval capabilities. CBIR is a method that aims to minimize the gap between the image feature set and human visual understanding to recognize the batik pattern. This survey reviews recent instance retrieval works developed based on handcrafted featured extraction and deep learning algorithms. The survey is organized by the most dataset, the most used method, and the survey method with the best performance. This survey highlights recent works, the potential of using handcrafted feature extraction and deep learning algorithms in CBIR, and the promising future prospects in this field.