JPS58163080A - Feature extracting system of character - Google Patents
Feature extracting system of characterInfo
- Publication number
- JPS58163080A JPS58163080A JP57045847A JP4584782A JPS58163080A JP S58163080 A JPS58163080 A JP S58163080A JP 57045847 A JP57045847 A JP 57045847A JP 4584782 A JP4584782 A JP 4584782A JP S58163080 A JPS58163080 A JP S58163080A
- Authority
- JP
- Japan
- Prior art keywords
- rectilinearity
- distance
- circuit
- character
- circuits
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/17—Image acquisition using hand-held instruments
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Character Discrimination (AREA)
Abstract
Description
【発明の詳細な説明】
(す発明の技術分野
本発明は実時間手書き文字認識装置に係シ、とくに曲線
の部分の多いひらがな等の文字を高#1度に近似できる
特徴抽出方式に関するものである。[Detailed Description of the Invention] (Technical Field of the Invention) The present invention relates to a real-time handwritten character recognition device, and in particular to a feature extraction method that can approximate characters such as hiragana, which have many curved parts, to a high degree of #1. be.
(2)従来技術と問題点 従来の特徴抽出方式としては、たとえば小高。(2) Conventional technology and problems For example, Odaka is a conventional feature extraction method.
荒用、壇田2 「ストロークの近似点による手書き文字
のオンライン認識」、電子通信学会論文集80/2 V
ol J65D應2に発茨されたように、文字の(1)
ストロークの長さや曲が9とは無関係に、画数によって
代表点数が固定的に決められている。このため第2図に
示す構成は非常に簡単化され、タブレット1からの入力
データは代表点数が画数により固定化された%微抽出回
路2で特徴がマツチング回路乙に送られ、辞書4から読
出された候補文字と照合され距離がとられ判定が行なわ
れる。しかし、このような方法では第1図に示すように
、曲シのあるストロークをもつ文字「わ」■を入力した
場合、辞書から読出される候補文字は「わ」■と「れ」
■であり、■と■の距離のでる部分■は■のαと■のA
間の距離であシ、■と■の距離のでる部分■は■のbと
■の31間の距離である。Arayo, Danta 2 "Online recognition of handwritten characters using stroke approximation points", Proceedings of the Institute of Electronics and Communication Engineers 80/2 V
As was discovered in OL J65D 應2, the number of representative points is fixedly determined by the number of strokes, regardless of the length of the character's (1) stroke or the length of the song. For this reason, the configuration shown in FIG. 2 has been greatly simplified, and the input data from the tablet 1 is sent to the % fine extraction circuit 2 in which the number of representative points is fixed by the number of strokes, and the features are sent to the matching circuit B, which reads them from the dictionary 4. The candidate character is compared with the candidate character, the distance is taken, and a determination is made. However, with this method, as shown in Figure 1, when the character "wa" ■ with a curved stroke is input, the candidate characters read from the dictionary are "wa" ■ and "re".
■, and the part ■ where the distance between ■ and ■ appears is α of ■ and A of ■
The distance between ■ and ■ is the distance between ■ and ■.
このように、直線部分から計算された距離も、曲線部分
から計算された距離も同等に扱われてしまうからgd&
率が悪くなる。In this way, the distance calculated from a straight line part and the distance calculated from a curved part are treated equally, so gd&
rate becomes worse.
(3)発明の目的
本発明の目的は曲線の部分の多い文字を高精度に近似で
きる特徴抽出方式を提供することである。(3) Purpose of the Invention The purpose of the present invention is to provide a feature extraction method that can approximate characters with many curved parts with high accuracy.
(4)発明の構成
(2)
前記目的を達成するため、本発明の文字の特徴抽出方式
は実時間手書き文字g!*装置において、曲線部分の多
い文字の特徴抽出をする際、ストロークの直線度を計測
する手段と、少なくとも該手段によシ計測された直線度
に応じて抽出すべき代表点数を決定する手段とを設けた
ことを特徴とするものである。(4) Structure of the Invention (2) In order to achieve the above object, the character feature extraction method of the present invention is based on the real-time handwritten character g! *In the device, when extracting features of characters with many curved parts, a means for measuring the straightness of the stroke, and a means for determining the number of representative points to be extracted according to at least the straightness measured by the means. It is characterized by having the following.
(5)発明の実施例 手書文字、とくにひらがなの場合には6う−ら”。(5) Examples of the invention Handwritten characters, especially hiragana, have six uras.
1わ−れ−ね′のように主に曲線部分に識別のための情
報が業中している。これに対し、従来は直線部分も曲線
部分も全く同じ個数の代表点で近似していた。しかし、
これでは本来本質的でない6う−ら”の11”の位[あ
るいは1わ−れ−ね”の61の位置の変化によ)%徴が
変ってしまい、本来識別のために有効な曲線部分の差異
が見えにくい。Identification information is mainly contained in curved parts, such as 1.Warene'. On the other hand, in the past, straight line portions and curved portions were approximated using exactly the same number of representative points. but,
In this case, the % mark changes due to a change in the 11" position of 6" which is not essential [or the 61st position of 1"], and the curve part that is originally effective for identification changes. It is difficult to see the difference.
そこで、本発明の原理は、代表点を抽出するに先立ちス
トロークの直線度を計算し、直線に近いストロークは少
ない点数で、曲線に近いストロークは多くの点数で近1
以することによって曲線スト(6)
ローフに重みをつけ、ひらがななどの曲線部分の多い文
字を高梢度で近似し4疏率を高めるようにしたものであ
る。Therefore, the principle of the present invention is to calculate the linearity of the stroke before extracting representative points, and strokes that are close to a straight line will have a small number of points, and strokes that are close to a curve will have a large number of points that are close to 1.
By doing this, weight is given to the curved stroke (6) loaf, and characters with many curved parts, such as hiragana, are approximated with a high degree of curvature, thereby increasing the 4-line rate.
45図(α) 、 (6)は上述の原理に従う実施例の
説明図であシ、同図(α)は構成図、同図(6)は要部
の詳細説明図である。45 (α) and (6) are explanatory diagrams of an embodiment according to the above-mentioned principle, FIG. 45 (α) is a configuration diagram, and FIG. 45 (6) is a detailed explanatory diagram of the main part.
同図(α)において、タブレット1から入力された文字
11v報は座標点系列として、直線度計測回路11に入
力される。ここで次に示す方法で直線度が計算される。In the same figure (α), the character 11v input from the tablet 1 is input to the straightness measuring circuit 11 as a coordinate point series. Here, linearity is calculated using the following method.
すなわち、同図(b)に示すように、曲線のストローク
S上代表点数のベクトルPI 、 P2・・・、Pnと
すると、直線度C,を次のようにだ義する。 ス)l=
−りSの延べ距離りは
とした場合、直線度C1は(1) 、 (2)よシでめ
る。C1は0≦C,≦1 の実数をもち1に近い(4)
はど直線に近い。That is, as shown in FIG. 3B, if vectors PI, P2, . . . , Pn are representative points on the stroke S of the curve, then the straightness C is defined as follows. s)l=
- If the total distance of the strip S is , then the straightness C1 can be calculated by (1) and (2). C1 has a real number of 0≦C, ≦1 and is close to 1 (4) is close to a straight line.
この直線度C1と代表点数の1例は次表に示される。An example of the linearity C1 and the number of representative points is shown in the following table.
表
同図(8)に戻9、直線度計測回路11で上述の方法に
よシ直線度C,が計算され、その値は上表の内容を格納
したIf線匿/代表点数変換テーブル12への入力とな
る。そして直線度に応じた代表点数を両特徴抽出回路1
6と14に送る。特徴抽出回路13ではタブレット1か
らの入力データを変換テーブル12からの代表点数に従
って特徴系列を抽出する。また特徴抽出回路14も辞1
iiF4から続出したデータを変換テーブル12からの
代表点数に従って特徴系列を抽出する。マツチング回路
3は特徴抽出回路15(5)
と14から送られてきた特徴系列を比較し、距離が最小
のカテゴリを答として送出する。距離を求めるには、
人力データの特徴系列 ””(2X1y Z2+・・・
π1)カテゴリjの辞書の特徴系列Xj=(z!jr
W2j+・・・ff1Jとすると、距離dj=Σ1町−
町j1
11+1
となる。Returning to table (8) in the same figure, 9, the linearity measurement circuit 11 calculates the linearity C, using the method described above, and the value is sent to the If linearity/representative point conversion table 12 that stores the contents of the above table. becomes the input. Then, both feature extraction circuits 1 calculate the number of representative points according to the linearity.
Send to 6 and 14. The feature extraction circuit 13 extracts a feature series from the input data from the tablet 1 according to the number of representative points from the conversion table 12. Also, the feature extraction circuit 14 is
ii A feature series is extracted from the data successively generated from F4 according to the number of representative points from the conversion table 12. The matching circuit 3 compares the feature sequences sent from the feature extraction circuits 15 (5) and 14, and sends out the category with the smallest distance as the answer. To find the distance, use the human data feature series “” (2X1y Z2+...
π1) Dictionary feature series Xj=(z!jr
If W2j+...ff1J, distance dj=Σ1 town-
Town j1 11+1.
第4図は本発明の他の実施例の構成を示す説明図である
。FIG. 4 is an explanatory diagram showing the configuration of another embodiment of the present invention.
46図の実施例ではストロークの直線度のみを代表点数
のパラメータとしたが、この実施例ではストp−りの長
さを組合せたものをパラメータとしたものである。In the embodiment shown in FIG. 46, only the linearity of the stroke is used as a parameter for the number of representative points, but in this embodiment, the parameter is a combination of the length of the stroke.
同図において、直線度/代表点数変換テーブル12の代
シに代表点数決定回路16を設け、入力データを直線度
計測回路11と並列に新たにストローク長計測回路15
を設け、ストローク長を直線度とともに代表点数決定回
路16に入力して、代表点数を決定するものである。そ
の効果は前実施例と同様である。In the same figure, a representative point number determining circuit 16 is provided in place of the straightness/representative point number conversion table 12, and a new stroke length measuring circuit 15 is added to input data in parallel with the straightness measuring circuit 11.
The number of representative points is determined by inputting the stroke length together with the linearity to the representative point number determining circuit 16. The effect is similar to the previous embodiment.
(6)発明の詳細
な説明したように、本発明によれば、ひらがな等の曲線
部分の多い文字の特徴抽出をする際、ストロークの直線
度を抽出し、少なくともこの直線度に応じて代表点数を
決定する手段を設けることによシ、文字を高精度に誤)
なく認識することが可能となる。(6) As described in detail, according to the present invention, when extracting the features of characters with many curved parts, such as hiragana, the straightness of the stroke is extracted, and at least the number of representative points is determined according to this straightness. By providing a means to determine the characters (with high precision)
It becomes possible to recognize the information without any problems.
第1図は従来例の問題点の説明図、第2図は従来例の構
成説明図、第6図(α) 、 (b)は本発明の実施例
の構成説明図と要部の詳細説明図、第4図は本発明の他
の実施例説明図であシ、図中1はタブレット、3はマツ
チング回路、4は辞書、11は直線度計測回路、12は
直線度/代表点数変換テーブル、15、14は特徴抽出
回路、15はストローク長計測回路、16は代表点数決
定回路を示す。
特許出願人富士通株式会社
復代理人 弁理士 1)坂 善 重
(7)
第1図
第2図
第3図
(a)
第4図Fig. 1 is an explanatory diagram of the problems of the conventional example, Fig. 2 is an explanatory diagram of the configuration of the conventional example, and Figs. 6 (α) and (b) are an explanatory diagram of the configuration of the embodiment of the present invention and detailed explanation of the main parts 4 are explanatory diagrams of other embodiments of the present invention, in which 1 is a tablet, 3 is a matching circuit, 4 is a dictionary, 11 is a linearity measurement circuit, and 12 is a linearity/representative point conversion table. , 15 and 14 are feature extraction circuits, 15 is a stroke length measurement circuit, and 16 is a representative point number determination circuit. Patent applicant Fujitsu Ltd. sub-agent Patent attorney 1) Yoshishige Saka (7) Figure 1 Figure 2 Figure 3 (a) Figure 4
Claims (1)
字の特徴抽出をする際、ストロークの直線度を計測する
手段と、少なくとも該手段によシ計測された直線度に応
じて抽出すべき代表点数を決定する手段とを設けたこと
を特徴とする文字の荷原抽出方式。In a real-time handwritten character recognition device, when extracting features of a character with many curved parts, there is provided a means for measuring the straightness of a stroke, and at least a number of representative points to be extracted according to the straightness measured by the means. 1. A method for extracting a character source, characterized in that it includes a means for determining.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP57045847A JPS58163080A (en) | 1982-03-23 | 1982-03-23 | Feature extracting system of character |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP57045847A JPS58163080A (en) | 1982-03-23 | 1982-03-23 | Feature extracting system of character |
Publications (2)
Publication Number | Publication Date |
---|---|
JPS58163080A true JPS58163080A (en) | 1983-09-27 |
JPH0149999B2 JPH0149999B2 (en) | 1989-10-26 |
Family
ID=12730600
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP57045847A Granted JPS58163080A (en) | 1982-03-23 | 1982-03-23 | Feature extracting system of character |
Country Status (1)
Country | Link |
---|---|
JP (1) | JPS58163080A (en) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP0151316A2 (en) * | 1983-12-26 | 1985-08-14 | Hitachi, Ltd. | On-line recognition method and apparatus for a handwritten pattern |
JPS60217482A (en) * | 1984-04-12 | 1985-10-31 | Toshiba Corp | Recognizer of character |
US4809195A (en) * | 1985-04-26 | 1989-02-28 | Battelle Memorial Institute | Storing and reconstituting analog signals using data compression |
JPH04177485A (en) * | 1990-11-07 | 1992-06-24 | Matsushita Graphic Commun Syst Inc | Character recognizing device |
-
1982
- 1982-03-23 JP JP57045847A patent/JPS58163080A/en active Granted
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP0151316A2 (en) * | 1983-12-26 | 1985-08-14 | Hitachi, Ltd. | On-line recognition method and apparatus for a handwritten pattern |
JPS60217482A (en) * | 1984-04-12 | 1985-10-31 | Toshiba Corp | Recognizer of character |
US4809195A (en) * | 1985-04-26 | 1989-02-28 | Battelle Memorial Institute | Storing and reconstituting analog signals using data compression |
JPH04177485A (en) * | 1990-11-07 | 1992-06-24 | Matsushita Graphic Commun Syst Inc | Character recognizing device |
Also Published As
Publication number | Publication date |
---|---|
JPH0149999B2 (en) | 1989-10-26 |
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