Picture Editor Using Color Attribute Encoding for Image Retrieval
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Solution Overview
Problem
Existing picture selection processes, such as those using thumbnail displays, are time-consuming and inefficient, especially when trying to find specific images with desired brightness, saturation, and hue, as users must manually scroll through numerous pictures to find the best match.
Innovation Solution
A picture editor that analyzes color pictorial data to extract and encode pictorial information on brightness, saturation, and hue, allowing for the automatic retrieval and display of images matching specified criteria, thereby streamlining the selection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pictures are displayed as thumbnails in an m x n array for selection, then the pictures can be viewed and selected, but it takes much time to select the desired picture as users must manually scroll through all pictures
Solution Approach 1:
The system performs preliminary analysis of all pictures to extract and encode pictorial information (brightness, saturation, hue) before the user needs to select. This pre-processing allows the system to quickly retrieve and display only the pictures matching the user's criteria, eliminating the need for manual scrolling through all thumbnails.
Solution Approach 2:
The manual mechanical scrolling process is replaced with an automated information retrieval system. Instead of physically moving through thumbnails, the system uses encoded pictorial information to automatically search and display matching pictures, substituting mechanical navigation with computational retrieval.
2Loss of information
If all pictures are displayed as thumbnails, then users can see multiple pictures at once, but it is not clear whether a specific picture has the desired brightness, saturation, and hue characteristics
Solution Approach 1:
The system extracts key pictorial information (brightness, saturation, hue) from each picture and encodes it separately. This extraction allows the system to present this information in a structured, searchable format, making it easy to detect and measure specific color characteristics without requiring users to visually inspect each thumbnail.
Solution Approach 2:
The system transforms visual pictorial characteristics into quantifiable parameters (brightness, saturation, hue values). By converting qualitative visual properties into measurable parameters, the system enables precise detection and comparison of color characteristics across multiple pictures.
3Ease of operation
If manual cursor movement is used to navigate through pictures, then users can select pictures, but the process is time-consuming especially when the desired picture is in the last position
Solution Approach 1:
Manual cursor navigation is replaced with automated information retrieval based on encoded pictorial data. The system uses the stored brightness, saturation, and hue codes to directly locate and display matching pictures, eliminating the mechanical process of moving the cursor through each picture in sequence.
Solution Approach 2:
The encoded pictorial information acts as an intermediary between the user's selection criteria and the actual picture data. Instead of directly navigating through pictures, the system uses the intermediate coded information to efficiently bridge the gap between user requirements and picture retrieval.
Data Source
AI summary
It is intended to provide a picture editor which displays the color pictorial data matching designated pictorial information, according to pictorial information code of the analyzed color pictorial data of a plurality of color pictures added to the color pictorial data, picks out and displays the color pictorial data matching designated pictorial information. For this purpose, the information code of each pictorial information on brightness, saturation, and hue of the color pictorial data, which is analyzed, digitized, and averaged in a pictorial data analyzing unit, is added to the color pictorial data in a retrieval information adding unit. According to the color pictorial data to which the information code is added, a retrieving unit picks out the color pictorial data matching designated pictorial information. A video monitor displays the retrieved color pictorial data.