Image Packing Canvas Fragmentation and Cell Merging
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Solution Overview
Problem
Current digital imaging technologies are limited in efficiently packing images of varying sizes and aspect ratios without cropping, obscuring, or overlapping, especially when images are from different sources or captured with different orientations.
Innovation Solution
A method and device that utilize an image placement module to determine the canvas orientation, fragment it into cells, merge cells vertically and horizontally, and resize images to fit perfectly within these cells, ensuring no empty space and maintaining original aspect ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated packing techniques are used to pack images of varying sizes and aspect ratios, then packing efficiency is improved, but images must be cropped, obscured, or overlapped to achieve effective packing
Solution Approach 1:
The canvas is divided into a grid of cells with dimensions matching the largest image's aspect ratio. This segmentation allows images to be placed in predefined regions without overlapping or cropping, as each cell is specifically sized to accommodate images of a particular orientation and aspect ratio.
Solution Approach 2:
Multiple images of different sizes and orientations are nested within the canvas by placing them in appropriately sized cells. The method nests portrait and landscape images together in a systematic arrangement, allowing efficient use of space while maintaining each image's complete integrity.
2Manufacturing precision
If manual packing is used to arrange images in an artistic manner, then image integrity is preserved, but time consumption increases significantly
Solution Approach 1:
The method performs preliminary actions by automatically sorting images into portrait and landscape categories, determining the aspect ratio of the largest image, and pre-calculating the grid dimensions before actual packing. This preliminary preparation enables rapid automated packing without compromising image integrity or artistic arrangement.
Solution Approach 2:
The packing algorithm dynamically adjusts the grid configuration based on the input images' characteristics (orientations, aspect ratios). It automatically determines the number of rows and columns needed to accommodate all images while maintaining their original dimensions, providing an adaptive solution that works for any set of images.
3Productivity
If current automated packing techniques are used for images from different sources with different orientations, then packing speed is improved, but significant portions of images are cropped or obscured
Solution Approach 1:
The method applies different treatment to different regions of the canvas based on image orientation. Portrait images are placed in cells optimized for vertical orientation, while landscape images are placed in cells optimized for horizontal orientation. This local quality approach ensures that each image is displayed in its optimal orientation without cropping or obscuring any content.
Data Source
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AI summary
A method and apparatus are provided for packing a plurality of images. A number of cells of a canvas on which the plurality of images having different aspect ratios are to be packed is determined. The cells on the canvas are merged such that a number of the plurality of images is equal to the number of the cells. Each of the plurality of images are placed in a corresponding one of the plurality of cells of the canvas, according to respective aspect ratios of the plurality of images, when the number of the plurality of images is equal to the number of the cells.