PowerPoint Presentation

Image processing- Meaning retrieval of word in an image.Under the guidance of:S. Naveen kumar(Asst.Professor)

Contents:AimIntroduction Software usedBlock diagramPros and consApplicationsWork divisionConclusion

AimThe input for this application will be an image of a word . The relative meaning of that word will be retrieved from the database and displayed.

IntroductionThe whole world is now wanting accuracy with speed. 'Image sensing and processing' is one of those techniques to achieve this goal. QR scanning, Image cryptography, security issues are some of the applications. The input for this technique is an image and the output will be a processed image or information related to that input image. Software requiredMATLABThe whole process is divided into three phases:Image detection using Mat Lab.Creating a Data Base of meanings.Connecting the output of Processed Image with the DataBase and retrieving the meaning of the word.STARTDISPLAY THE DATA AS THE FINAL INPUTIDENTIFY THE REGION OF THE IMAGE WHERE TEXT IS PLACEDTERMINATE THE APPLICATIONALLIGN THE IMAGE OF PROPERLY NOT ALLIGNEDRETRIVE CORRESPONDING DATA FROM THE DATA BASEMAKE THIS TEXT AN INPUT TO A DATA BASECONVERT THE IMAGE IN TO EDITABLE TEXTCAPTURE AN IMAGE OF A WORDPROCESS THE IMAGEBLOCK DIAGRAMSteps involvedReading the image.Segmentation.Converting to binary image.Trimming the image.Normalization.Classification.Comparison with templates.Text extraction.

Loading the imageLoad the image into Mat Lab. If the image is not properly aligned, it can be rotated in plane, but significant out of plane rotations may require additional pre-processing.

Commands: colorImage = imread('handicapSign.jpg'); figure; imshow(colorImage); title('Original image')Next Step: SegmentationThe image is cropped to fit the text.The noise in images is removed by cropping the part of the image which has textAfter that, line by line is separated.

Example : To convert any image into Binary imageThe threshold for the binary image transformation is 0.99 (= bn im2bw (image, 0.99)).This threshold was taken to colors with close to 255 (maximum) RGB values are considered as 0 in the binary image.Trimming the imageThe parts of the image which have text are to be trimmed. This is shown in the next slide.The next step is to separate each line.Once obtained separately each line of the image, it is necessary to remove one letter from the image matrix fl.For this function the bwlabel used, which label connected components of the image.In other words, this function has the solid lines and lists. Example :

NormalizationThen each letter is normalized to a size of 42 x 24 pixels, which is the size of the template that will perform the co-relation. This technique is formally is known as normalization.TemplatesEach template is a binary image bmp 42 x 24 pixels. They are stored separately so that they can be used for reference.Final stepThen the image is compared with templates and most approximate results are stored as outputs.With this step, image processing part is done and the final text is extracted is given as input the database for retrieval.Real-time Applications Image processing is a labor camp absolutely crucial for those groups and industries that are working in areas such as medical diagnosis, astronomy, geophysics, environmental sciences, data analysis in laboratories, Industrial inspection, etc. To sort out the posts according to their destination by reading their address present on their envelope this makes sorting faster and accurate In banking services for reading the amount and name of the person present on the cheque, DD etcOld scripts can be stored digitally so that they can be reproduced when ever needed.The same principle can be used for number plate recognition and in the name card reader.AdvantagesThe main advantage is when ever there is huge data in the form of image then the text in that can be extracted easilyLimitationsBlack colored text printed on white sheet is preferred for maximum accuracy.No extra light effects must be present while capturing the image.Font style variation must be avoided through out the text.It is difficult to differentiate between characters such as I&i, S&s, Z &z. Font of text taken as input must match with font of database images for better accuracy.Test Example