左カメラ左光源 Z Y 書籍 右カメラ 右光源 X-Y Z X 1: 2 [9 12] [12] NURBS 1 NURBS X-Y [13,14] Hough [15] [13, 14] [15] Structure from motion NURB

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1 Correction of Distorted Document Images Using a Stereo Vision System,, Yusuke SUZUKI Atsushi YAMASHITA and Toru KANEKO : {f ,tayamas,tmtkane}@ipc.shizuoka.ac.jp 1 [4,5] [1] 3 1 OCR Shape from shading [2, 3] Shape from shading [6,7] 3 [8] 1

2 左カメラ左光源 Z Y 書籍 右カメラ 右光源 X-Y Z X 1: 2 [9 12] [12] NURBS 1 NURBS X-Y [13,14] Hough [15] [13, 14] [15] Structure from motion NURBS NURBS B Q ij (0 i m 1, 0 j n 1) u, v P (u, v) (1) m 1 n 1 w ij B i,k (u)b j,k (v)q ij i=0 j=0 P (u, v)= m 1 n 1 1 w ij B i,k (u)b j,k (v) (1) i=0 j=0 B i(j),k K B w B 1 NURBS [16] 2

3 左カメラ 法線 右カメラ 左画像 書籍 右画像 2: 3 X-Y Z Z X, Y 2.3 NURBS 4 2 N r i m i h Verlet t i(=1 N) r i (t + h) = 2r i (t) r i (t h) + h2 m i F i (t) (2) F i (t) t i F i (t) = k(r i (t) r i (t h)) + F G + (F T ) i (3) k F G Z (F T ) i X-Y (2) (3) h r i Z T 3: 鏡面反射鏡面反射 (a) 左照明 (b) 右照明 4: P (x, y, z) P ψ Phong P ψ I h (x, y, z) (4) I h (x, y, z) = I in (x, y, z)k d cos n ψ (4) I in (x, y, z) P k s n k s n (4) ψ I h ψ 0 ψ < ψ 0 I h 3

4 書籍 r P(x,y,z) S 光源 5: (i, j) 3 (x, y, z) I(i, j) 4 I max (i, j) I(i, j)/i max C(i, j) I max /I(i, j) RAW 2 NURBS P (x, y, z) I(x, y, z) (5) cos θ I(x, y, z) = k d I q r 2 cos ϕ ds (5) S (5) (5) (i, j) I(x, y, z) (i, j) (x, y, z) 4 (5) k d I q S θ r P ϕ k d I q r 2 θ P P (a) (b) (c) (d) 6: pixels 4

5 (a) 照明方向変化画像 (b) 除去結果 図 7: 紙面形状復元結果 1 図 9: 鏡面反射除去結果 (a) 補正前 左画像 右画像 (b) 補正後 図 8: 歪み補正結果 1 図 10: 最終結果 次に 鏡面反射の除去結果を図 9 に示す (a) の画 果からも 本手法の有効性が確認できる 像は 上が左照明 下が右照明の画像である 照明 方向変化に伴い鏡面反射位置も変化している これ らの画像を合成することにより失われたテクスチャ 5 情報を補完し (b) の結果が得られる 最終結果を図 10 に示す 各種処理により文字の歪 結論 本研究では ステレオカメラを用いた文書画像の み 鏡面反射 陰影が補正されている 歪み補正手法を提案した ステレオ計測結果に基づ 別のドキュメントに対しても同様の実験を行った き 文字の傾きや歪みといった幾何学的歪みを補正 折りたたみ文書のステレオ画像対を図 11 に 形状復 した その際 ステレオ画像合成処理により低解像 元および歪み補正の結果を図 12 図 13 に示す 上 度領域を補完し より高精細な画像を作成した ま の結果と同様 歪んだ文字列を補正することができ た 紙面上での光の反射を計算することにより 陰 ている 実験結果より本手法の有効性が確認できた 影や鏡面反射といった光学的歪みの補正も行った 結果の評価のために 市販の OCR ソフトを用いた 今後の課題として 歪み補正の更なる高精度化や 文字認識実験を行った 結果を表 1 に示す (a),(b) 処理の高速化が挙げられる はそれぞれ補正前後の実験画像 (c) は書籍を物理的 に平らな状態に変形させて取得した画像である 補 謝辞 本研究の一部は 文部科学省科学研究費補助金 正処理により認識率が著しく向上しており 平面状 若手研究 (B) の援助を受けた 態の文字認識率とほぼ等しくなっている 以上の結 参考文献 表 1: 文字認識実験結果 画像 (a) 補正前 (b) 補正後 (c) 平面状態 [1] 樫村雅章 歴史的に貴重な本のデジタルアーカイブ O plus E, vol.27, no.10, pp , 文字認識率 63.6% 97.3% 98.4% [2] T.Wada, H.Ukida and T.Matsuyama: Shape from Shading with Interreflections Under a Proximal Light Source, International Journal of Computer Vision, vol.24, no.2, pp ,

6 (a) 左画像 (a) 補正前 (b) 右画像 図 11: 折りたたみ文書ステレオ画像 左画像 右画像 (b) 補正後 図 12: 紙面形状復元結果 2 [3] C.L.Tan, L.Zhang, Z.Zhang and T.Xia: Restoring Warped Document Images through 3D Shape Modeling, IEEE Trans. Pattern Analysis and Machine Intelligence, vol.28, no.2, pp , [4] 黄瀬浩一 大町真一郎 内田誠一 岩村雅一 カメラ を用いた文字認識 文書画像解析の現状と課題 信学 技報, vol.104, no.742, pp.85-90, [5] J.Liang, D.Doermann and H.Li: Camera-Based Analysis of Text and Documents: a Survey, International Journal on Document Analysis and Recognition, vol.7, no.2-3, (c) 補正後 全体 図 13: 歪み補正結果 2 [6] S.I.Cho, H.Saito and S.Ozawa: Shape Recovery of Book Surface Using Two Shade Images Under Perspective Condition, 電学論 C, vol.117-c, no.10, pp , [13] A.Ulges, C.H.Lampert and T.Breuel: Document Capture Using Stereo Vision, Proc ACM Symposium on Document Engineering, pp , [7] F.Courteille, A.Crouzil, J.D.Durou and P.Gurdjos: Towards Shape from Shading Under Realistic Photographic Conditions, Proc. 17th International Conference on Pattern Recognition, vol.2, pp , [14] A.Yamashita, A.Kawarago, T.Kaneko and K.T.Miura: Shape Reconstruction and Image Restoration for Non-Flat Surfaces of Documents with a Stereo Vision System, Proc. 17th Interna[8] 天野敏之 安部勉 西川修 伊與田哲男 佐藤幸男 tional Conference on Pattern Recognition, vol.1, アイスキャナによる湾曲ドキュメント撮影 信学論 pp , (D-II), vol.j86-d-ii, no.3, pp , [15] T.Sato, A.Iketani, S.Ikeda, M.Kanbara, [9] M.Pilu: Undoing Paper Curl Distortion Using ApN.Nakajima and N.Yokoya: Mobile Video Mosaicplicable Surfaces, Proc. 8th IEEE Computer Sociing System for Flat and Curved Documents, Proc. ety Conference on Computer Vision and Pattern 1st International Workshop on Mobile Vision, Recognition, pp.67-72, pp.78-92, [10] H.Cao, X.Ding and C.Liu: A Cylindrical Surface [16] L.Piegl and W.Tiller: The NURBS Book 2nd EdiModel to Rectify the Bound Document Image, tion, Springer-Verlag, New York, Proc. 9th IEEE International Conference on Computer Vision, pp , 鈴木優輔 静岡大学大学院工学研究科修士課程に在籍 ス [11] M.S.Brown and W.B.Seales: Image Restoration of Arbitrarily Warped Documents, IEEE Trans. Pattern Analysis and Machine Intelligence, vol.26, no.10, pp , テレオビジョンを用いた書籍画像補正技術の研究に従事 [12] M.S.Brown and Y.C.Tsoi: Geometric and Shading Correction for Images of Printed Materials Using Boundary, IEEE Trans. Image Processing, vol.15, no.6, pp , 金子透 静岡大学工学部機械工学科教授 画像処理 コン 山下淳 静岡大学工学部機械工学科助教 コンピュータビ ジョン ロボットの知能化に関する研究に従事 ピュータビジョンの研究に従事 6

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