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How to Classify Image Object

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2015-08-31

Easy to use, but seems like a lot of steps to go through to get to the documents and to save them to my computer. I have to save it to my computer to print it because printing from the program doesn't get it all printed on the 8.5x11" paper so leaves information off.

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My wife had some US Government forms that needed to be filled out and returned. Because of her medical condition, she couldn't fill them out longhand, and she asked me if there was a way she could type and fill them in. We couldn't find access to a typewriter (WHAT'S THAT???), but I searched on Google and found information about your app. I had worked with some PC-based forms applications before, so I knew what type of function I was looking for. I scanned the forms into a PDF, and PDFfiller opened the files and allowed me to create editable fields on the forms which she then filled using your browser-based app. It got the job done! There were a couple times where she thought she had lost everything, but because of the automatic save function, nothing was lost. Unfortunately, I don't have any other immediate need for this, but I certainly hope you use this for promoting your product. I would have given it 5 stars had there been an apparent way of copying all the fields I added to one page and paste them onto identical subsequent pages in my document (you know the Government--lots of duplicate type information!). I had to create the same fields over about 8 or 9 identical pages on one of the forms. If I find I do have more use for this app in the near future, I will purchase it!

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What is object classification in image processing?

Image Classification helps us to classify what is contained in an image. Image Localization will specify the location of single object in an image whereas Object Detection specifies the location of multiple objects in the image. Finally, Image Segmentation will create a pixel wise mask of each object in the images.

What is object based image classification?

Object-based Classification. Object-based classification is a two-step process, first the image is segmented or broken into discrete objects or features with and then each object is classified. This type of classification attempts to mimic the type of analysis done by humans during visual interpretation.

What is object based image analysis?

Object-based image analysis (OBI) involves pixels first being grouped into objects based on either spectral similarity or an external variable such as ownership, soil or geological unit.

What is meant by image classification?

Image classification refers to the task of extracting information classes from a multiband raster image. The resulting raster from image classification can be used to create thematic maps. The recommended way to perform classification and multivariate analysis is through the Image Classification toolbar.

What is the purpose of image classification?

The objective of image classification is to identify and portray, as a unique gray level (or color), the features occurring in an image in terms of the object or type of land cover these features actually represent on the ground.

What is unsupervised image classification?

Unsupervised image classification is the process by which each image in a dataset is identified to be a member of one of the inherent categories present in the image collection without the use of labelled training samples.

What is classification in image processing?

Image classification refers to a process in computer vision that can classify an image according to its visual content. For example, an image classification algorithm may be designed to tell if an image contains a human figure or not. An algorithm such as SURF is used to generate features.

What is image classification used for?

The objective of image classification is to identify and portray, as a unique gray level (or color), the features occurring in an image in terms of the object or type of land cover these features actually represent on the ground. Image classification is perhaps the most important part of digital image analysis.

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