Binarization Threshold Adjustment Using Histogram Mound Detection
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Solution Overview
Problem
Conventional binarizing processes often fail to accurately convert characters with colors close to the background into black pixels, leading to character disappearance or character collapse in binarized images, due to inappropriate threshold value settings.
Innovation Solution
An image processing apparatus and method that generates histogram index values, detects mound-shaped parts in the histogram, adjusts the threshold value based on these features, and applies a binarizing process using the adjusted threshold to ensure accurate conversion of pixels into white or black pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional binarizing process with fixed threshold value is used, then the processing speed is fast and the process is simple, but characters with colors close to the background cannot be accurately converted, leading to character disappearance or collapse
Solution Approach 1:
The patent applies preliminary actions by performing histogram analysis and detecting mound-shaped parts before the actual binarization process. The threshold value is adjusted based on the detected mound-shaped parts in advance, ensuring that characters with colors close to the background are correctly identified before conversion to binary values, thereby preventing character disappearance or collapse
Solution Approach 2:
The patent changes the threshold value parameter dynamically based on the histogram analysis. Instead of using a fixed threshold, the system adjusts the threshold value according to the detected mound-shaped parts in the histogram, which represents the distribution of pixel brightness values. This parameter change enables accurate differentiation between characters and background even when their colors are similar
2Measurement precision
If the threshold value is adjusted using conventional offset methods, then some improvement in character recognition is achieved, but desired results cannot be obtained for all image data, particularly for characters with background-like colors
Solution Approach 1:
The patent applies local quality by analyzing the specific characteristics of the histogram for each image and detecting mound-shaped parts that represent local distributions of pixel values. Instead of applying a universal offset to the threshold, the system identifies specific regions in the histogram (mound-shaped parts) that correspond to character or background pixels and adjusts the threshold locally based on these detected features, enabling accurate binarization for diverse image types
Solution Approach 2:
The patent implements feedback by using the histogram analysis results to continuously adjust the threshold value. The system detects mound-shaped parts in the histogram, determines the appropriate threshold adjustment based on these detections, and applies the adjusted threshold to the binarization process. This feedback mechanism ensures adaptability to different image types and achieves desired binarization results across various scenarios
Data Source
AI summary
An image processing apparatus has a color image, the image data being constituted by multiple pixels, each of the multiple pixels having a gradation value, and a controller, which is configured to generate a histogram of index values corresponding to brightness values of the multiple pixels constituting the image data, set an original threshold value based on the histogram which is referred to for binarization, detect a mound-shaped part, in the histogram, satisfying a particular condition, set an adjusting direction in which the original threshold value is to be adjusted, set the index value at a base on a particular direction side of a particular mound-shaped part which is one of mound-shaped parts existing on the adjusting direction side with respect to the original threshold value in the histogram as an adjusted threshold value, and apply a binarizing process to the image data using the adjusted threshold value.