1. A system for analyzing digital forensic evidence using an image filter, comprising: a duplicator that creates a copy of digital evidence; a verifying unit that verifies whether the copy created by the duplicator is identical to the original of the digital evidence; an evidence analyzer that classifies image files of the copy of the digital evidence into predetermined categories, using the image filter including an image filtering model created by a learning model, and then analyzes the evidence; and a reporting unit that creates a report about the evidence analysis result obtained by the evidence analyzer, wherein the evidence analyzer analyzes not only existing data and image files on a hard disk, but also images restored from deleted and lost data and performs registry analysis, e-mail analysis, web history analysis, password analysis, and related keyword search analysis wherein the learning model improves an accuracy of the classifying by learning more samples using resources in advance, wherein the evidence analyzer includes: an image evidence analyzer that analyzes image evidence included in the copy of the digital evidence, an image file extractor that extracts all of the images included in the copy of the digital evidence; an image filtering model learning unit that receives learning sample images classified into predetermined categories, performs a pre-process, including removing image frames or separating multi-images, and creates an image filtering model on the basis of characteristics, including color and tone, which represent image properties extracted from the pre-processed learning sample images and a learning algorithm, and an image filter that receives image files extracted by the image file extractor, filters the image files into predetermined categories using the image filtering model created by the image filtering model learning unit, and then outputs the analysis result of the image classified into the predetermined categories.