解決方法:
將自己想要轉化文字的圖片保存到手機相冊中→打開手機上的QQ→點擊右上角的加號,找到掃一掃點擊→在頁面右上角點擊相冊→找到想要轉化的圖片並點擊確定→即可轉化為文字→復制到word中即可
方法步驟:
1.將自己想要轉化文字的圖片保存到手機相冊中,例下圖;
2. 如何把圖片里的文字轉換成word
要做到這一點,需要使用Office 2003里自帶的Document Imaging工具。因為必須有了它才能將文字從圖片里「摳」出來,然後將掃描文件轉換成Word。
具體步驟如下:
1、在【開始】菜單的「Microsoft Office工具」中打開Microsoft Office Document Imaging。
2、在左側窗口中單擊滑鼠右鍵,選擇「粘貼頁面」,把復制的圖片粘貼到Document Imaging中。
3、在「工具」中選擇「使用OCR識別文本」,Document Imaging的OCR識別程序就會對圖片進行識別。
4、上一步完成後,選擇「工具」中的「將文本發送到Word」,程序會自動打開Word文檔,這時展現在用戶面前的就是從圖片中「摳」出來的文字了。
提示:一般而言,識別的准確率可以達到95%以上,但對英文和數字的識別不是太好。
另外請注意:許多用戶第一次使用該工具時都需要安裝,安裝的時候插入Office安裝盤即可。如果安裝不行的話,那就只能到網上去找找其他的「文字識別系統」了。
3. 如何將圖片內容轉換成WORD文檔
如果題主是在電腦上識別的話,可以下載關於OCR文字識別的軟體。我使用的是風雲OCR文字識別所以就以這款軟體為示例了。
在電腦上安裝軟體打開後,我們點擊左上角的單張圖片識別功能
這時你就可以在文檔上面修改了。注意輸出格式要修改為Word文檔格式輸出。
4. 圖片文字轉換成Word的方法
圖片轉換成word文檔的方法:
運行OCR文字識別軟體,選擇高級識別選項
然後打開Word文檔,檢查識別效果即可,不對的地方可手動校正。
5. 如何將圖片上的文字轉換成word文檔
以WPS 2019版為例
1、打開文件,選中需要轉換的圖片,依次點擊「特色應用」—「圖片轉文字」
6. 求大神將圖片上的文字轉換成word格式 在線等
幫你轉了,可惜解析度太低,將就用:
可以嘗試:OnlineOCR、NewOCR、Free OCR這些網站在線識別
下面是用Free OCR幫你識別的結果
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[-2- The use of exemplars rather than labels is an attempt by the proct-development
G mm» maintain as close a link as possible to the actual words by customers. For
§_= artample, one might label a group of statements about computer viewing devices as 「ap-
' 『 popriate ergonomics." but this may be misleading tithe customer really said 「everything
『 is blurred aher a day using my computer." The "blurred-vision" statement provides the
t team with more realistic clues about pmdllfl flit "ilk" "K Wliliuli
label does not.
11reData
h The groupconsensus chart for portable food-carrying devices was constructed by a
team of engineering manlumr chosen from M.l.T.'s Management of Technology Pro-
grant/l'heteam hadstudiedtheproct category. had read all ofthc interview transcripts.
and had reviewed the list of customer needs. The team was lead by Abbie Griffin. who
had observed and/or participated in almost 20 instry applications of group-consensus
charts at that time. Sixty M.l.T. graate students who use food-canying devices panic-
ipated in the customer sort. Because we funded this data collection ourselves. we reP°f\
the actual customer needs.
In addition we compared group-consensus charts and customer-sort hierarchies for 8
major consumer good with almost 200 customer needs Two g'0up-C0ltS¢l'tSttS charts
were developed: one by a team at the consumer-procts company who had worked on
the proct category. and mother by a team olgraate students from M.l.T.『s engineering
school. The customer-sort hierarchy was based on a sample of 60 consumers chosen
randomly from active users of the proct category. Because the data are proprietary,
we report summary statistics and our qualitative impressions only.
Finally. wereportonacomputer-proct application in wltichateam-based consensus
chart was compared to a customer-based consensus chart. and we report the qualitative
elperienoe of approximately 20 proprietary applications of the customer-sort
methodology.
I-『and-mn;viug Deviev Structures
Table I compares the top levels of the group-consensus chart and customer-sort hier-
archies for food-mnying devices (The complete hierarchies are available in Grithn l989.l
『 Consider first the number of secondary and tertiary needs and the number oi『 exemplars
It within each primary grouping. The customer-sort technique provides a more even dis-
『¥『 ._ uibution. While an even distribution rs no guarantee that a hierarchy is better. an even
'_ distribution is one of the desirable features for which proct-development teams look.
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