In-image similarity-based image structure descriptor and its applications

2018 Fiscal Year Final Research Report

• Project/Area Number: 15K00156
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Multimedia database
• Research Institution: Tokyo Metropolitan University
• Principal Investigator: Fujiyoshi Masaaki 首都大学東京, 学術情報基盤センター, 准教授 (20336522)
• Project Period (FY): 2015-04-01 – 2019-03-31
• Keywords: 類似性

Outline of Final Research Achievements

This study aimed at developing the image structure descriptor based on relations among similar areas in single image. First, several techniques for computing the similarity between two image pieces were investigated by applying techniques to various images. Unfortunately, the best technique for this study has not been decided because the techniques varied in the performance due to the size and content of images. Computing the similarities between any areas requires a huge computational cost, even if areas are in single image. Then, the similarities were calculated between feature points taken out by several techniques. Again, the best technique combination could not be figured out because the same reason. Besides these results, a method for automatic classification of photography composition has developed based on the results, and the method has been published.

Free Research Field

画像処理

Academic Significance and Societal Importance of the Research Achievements

目標とした構造記述子は，画像の不正編集検出などに有用であると考えられる．一方，研究遂行中に着想を得，関連研究として成果を公表した，風景写真構図の自動推定は，大量のディジタル写真を日々撮影し，データを蓄積する現在，保存あるいは共有などするに値する好ましい写真を自動的に選別する一助となり，利用者の負担を軽減する．従来，顔写真を対象とした技術しかなかったが，その範囲を風景にも広げている．