Patent Drafting Analysis of Electronics and Telecommunications Research Institute’s Hierarchical Histogram Equalization | US 2024/0249386 A1
Patent Drafting Analysis of Electronics and Telecommunications Research Institute's Hierarchical Histogram Equalization | US 2024/0249386 A1
A structural and strategic analysis of ETRI's hierarchical histogram equalization patent covering claim architecture, drafting quality, critical gaps, and prosecution positioning across apparatus and method claim types.
Spec Words
4,200
Across 6 sections
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Total Claims
17
3 independent · 14 dependent
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Figure Sheets
4
System block diagram, image division examples, pseudocode, process flowchart
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Published by PatSnap Insights Team · · 9 min read Verified by PatSnap Eureka Data
Overview
Structural Overview
The detailed description dominates at approximately 50% of total specification words (~2,100 of ~4,200), with the claims section accounting for a substantial ~25% — a ratio that reflects the method claims' verbose multi-step recitation style. The patent presents 17 claims across 3 independent claims (Claims 1, 7, and 13), yielding a 4.67:1 dependent-to-independent ratio within the normal range for image processing software patents. Figure coverage across 4 sheets spans hardware architecture, hierarchical division illustration, pseudocode implementation, and the full process flowchart, providing reasonably comprehensive visual support for the core embodiments.
Section Word Distribution
↗ Click bars to exploreFigure Inventory — 4 Sheets
| Figure | Description | Role |
|---|---|---|
| FIG. 1 | Block diagram of image processing apparatus 100 showing memory 110, input device 120, output device 130, and processor 140 interconnections.Search in Eureka ↗ | System architecture |
| FIG. 2A | Exemplified view of original input image 10 before hierarchical division, shown as an undivided rectangle.Search in Eureka ↗ | Claim support |
| FIG. 2B | Exemplified view showing first-level quadratic division of input image into four sub-images, with sub-image 10a requiring histogram equalization highlighted by hatching.Search in Eureka ↗ | Key embodiment |
| FIG. 2C | Exemplified view of second-level division showing sub-image 10a redivided into four second sub-images, with sub-image 10b requiring equalization and sub-image 10c highlighted.Search in Eureka ↗ | Key embodiment |
| FIG. 3 | Pseudocode listing showing Hierarchical_Histogram_Equalization and Histogram_Equalization recursive function calls implementing the hierarchical equalization algorithm.Search in Eureka ↗ | Key embodiment |
| FIG. 4 | Detailed flowchart of image processing method steps S402–S424, illustrating input, histogram analysis, division decisions, sub-image equalization, and recursive redivision logic.Search in Eureka ↗ | Flow diagram |
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Claims
Claim Architecture Analysis
The patent contains 3 independent claims: Claim 1 (apparatus), Claim 7 (method — simplified two-step version), and Claim 13 (method — full hierarchical multi-step version), providing both system and method coverage. The 14 dependent claims against 3 independent claims yields a 4.67:1 ratio, modestly below the 5–8:1 norm typical for image processing software patents in the G06T class. Notably, the claim strategy employs two distinct method independent claims — Claim 7 providing a simplified scope and Claim 13 a more detailed hierarchical recitation — which creates potential for broader enforcement but also introduces unnecessary redundancy that may complicate prosecution.
Core inventive concept: The claims address the problem of global histogram equalization degrading image quality in regions that do not need contrast enhancement, solved by a processor that hierarchically divides an input image, individually determines whether each sub-image "requires histogram equalization," and applies equalization selectively only to those sub-images that require it — as recited across Claims 1, 7, and 13.
Independent Claim Dissection
| Claim | Preamble | Transition | Key Body Elements |
|---|---|---|---|
| Claim 1 | An image processing apparatus | comprising | a memory; a processor connected to the memory; processor divides input image hierarchically; determines whether each sub-image requires histogram equalization; performs histogram equalization on sub-image that requires itSearch prior art ↗ |
| Claim 7 | An image processing method | comprising | determining whether histogram equalization is required for each sub-image while hierarchically dividing an input image; performing histogram equalization on a sub-image that requires histogram equalizationSearch prior art ↗ |
| Claim 13 | An image processing method | comprising | determining whether histogram equalization is required based on histogram of input image; determining whether input image requires division; dividing into plurality of first sub-images; determining whether equalization required for each first sub-image; when first sub-image requiring equalization exists and requires division, recursively dividing into second sub-images until sub-image size reaches preset reference size; performing equalization on qualifying sub-imagesSearch prior art ↗ |
Claim Dependency Tree
1 Apparatus: memory + processor that hierarchically divides image, determines equalization need per sub-image, applies selectivelySearch Claim 1 prior art ↗
2 Adds: processor divides in hierarchical structure until image reaches preset size; divides only sub-image requiring equalization in each hierarchySearch in Eureka ↗
3 Adds: processor determines equalization requirement based on histogram characteristics of each sub-imageSearch in Eureka ↗
4 Further: determination based on linearity of cumulative distribution function (CDF) of histogramSearch in Eureka ↗
5 Further: determination based on deviation between CDF graph and approximate straight line slope of CDFSearch in Eureka ↗
6 Adds: determination based on mean or standard deviation of histogram (depends on Claim 3)Search in Eureka ↗
7 Method: determining equalization need per sub-image while hierarchically dividing; performing equalization on qualifying sub-imageSearch Claim 7 prior art ↗
8 Adds: determination based on histogram characteristics of each sub-imageSearch in Eureka ↗
9 Further: determination based on CDF linearitySearch in Eureka ↗
10 Further: determination based on deviation between CDF graph and approximate straight line slopeSearch in Eureka ↗
11 Adds: determination based on mean or standard deviation of histogram (depends on Claim 8)Search in Eureka ↗
12 Adds: processor divides input image in hierarchical structure until preset size; divides only sub-image requiring equalization in each hierarchy (depends on Claim 7)Search in Eureka ↗
13 Method: full hierarchical recursive method — determine equalization need from input histogram; determine division need; divide into first sub-images; check each; recursively redivide until reference size; equalize qualifying sub-imagesSearch Claim 13 prior art ↗
14 Adds: processor also performs equalization on first sub-image not required to be divided among equalization-requiring first sub-imagesSearch in Eureka ↗
15 Further: determination based on CDF linearity (depends on Claim 14)Search in Eureka ↗
16 Further: determination based on deviation between CDF graph and approximate straight line slope (depends on Claim 15)Search in Eureka ↗
17 Adds: determination based on mean or standard deviation of histogram (depends on Claim 13)Search in Eureka ↗
| Metric | This Application | Software / Image Processing Norm |
|---|---|---|
| Total claims | 17 | 15 – 25 |
| Independent claim count | 3 | 2 – 4 |
| Dependent : Independent ratio | 4.67 : 1 | 5 – 8 : 1 |
| Method claims present? | Yes — Claims 7, 13 | Common |
| System / apparatus claims? | Yes — Claim 1 | Common |
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Drafting Quality
Drafting Quality Signals
The patent demonstrates solid specification-to-claim consistency anchored by FIG. 4's detailed flowchart and the pseudocode in FIG. 3, which directly support the method limitations of Claims 7 and 13. However, the filing's most notable weakness is its complete absence of a computer-readable medium (CRM) claim — a significant omission given that FIG. 3 explicitly discloses a software implementation using recursive function calls, leaving a major enforcement gap.
✅
Antecedent Basis
The claims are generally clean on antecedent basis. Claim 1 introduces "a memory" and "a processor" in the preamble/body and correctly uses "the processor" in the functional limitations. Claim 13's multi-step method claims introduce "first sub-images" before referencing "the first sub-images," and "second sub-images" is similarly introduced before use. No orphaned "the" references were identified across all 17 claims.
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Spec–Claim Consistency
FIG. 4 (steps S402–S424) maps precisely to the sequential limitations of Claim 13, covering histogram analysis, division determination, sub-image creation, recursive redivision, and selective equalization. FIG. 3's pseudocode directly supports Claims 7 and 1's functional language. Paragraphs [0046]–[0051] provide written description for the CDF linearity limitations in Claims 4, 5, 9, 10, 15, and 16. The specification–claim mapping is the strongest aspect of this filing.
✅
Transition Word Usage
All three independent claims correctly use "comprising" — the open-ended transition appropriate for this technology, allowing the claimed processor and method steps to coexist with additional memory, hardware components, or processing steps in accused products. No unnecessarily narrow "consisting of" or "consisting essentially of" transitions were used. This is the correct strategic choice for a software-implemented image processing patent where hardware implementations may incorporate additional components.
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§112(f) Means-Plus-Function Risk
No explicit "means for" language appears in the claims, mitigating direct §112(f) exposure. However, Claim 1's purely functional recitation — "the processor divides an input image hierarchically, determines whether each sub-image requires histogram equalization, and performs histogram equalization" — without structural constraints could attract a functional claiming challenge under §112(b) indefiniteness if an examiner argues the functional language does not adequately define the metes and bounds of the invention, particularly given the broad scope of "determines whether each sub-image requires histogram equalization."
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§101 Eligibility Risk
Claims 7 and 13 are method claims with no structural tie to hardware beyond a generic processor, presenting Alice Step 1 exposure as directed to an abstract idea of mathematical analysis (histogram CDF linearity, deviation measurement) applied to image data. The apparatus Claim 1 provides the strongest §101 defense by reciting a memory and processor, but the functional limitations closely mirror the method claims. A stronger filing would have anchored the independent claims to the specific hardware architecture shown in FIG. 1, or added a CRM claim to provide a distinct §101 vehicle.
⚠️
Dependent Claim Fallback Quality
The dependent claim structure exhibits significant redundancy: Claims 4/5/6 (depending from Claim 3 depending from Claim 1), Claims 9/10/11 (depending from Claim 8 depending from Claim 7), and Claims 15/16/17 (depending from Claims 14/13) all recite near-identical limitations — CDF linearity, CDF deviation, and mean/standard deviation tests — across three parallel claim chains. While this tripling provides some fallback, it wastes dependent claim slots on redundant coverage rather than adding genuinely distinct technical limitations such as specific division ratios, particular equalization algorithms (AHE, BBHE, DHE mentioned in [0053]), or output format limitations.
⚠️
Abstract Quality
The abstract — "the processor may divide an input image hierarchically, determine whether each sub-image requires histogram equalization, and perform histogram equalization on a sub-image that requires histogram equalization" — describes the hardware structure accurately but omits the key novel contribution: the CDF-linearity-based decision mechanism and the recursive hierarchical stopping condition (preset reference image size). An examiner reading only the abstract may not appreciate the CDF deviation analysis as the distinguishing feature over prior CLAHE/AHE art, potentially resulting in broader prior art searches being missed during prosecution.
✅
Figure Support Quality
FIG. 1 directly supports the memory/processor/input device/output device limitations of Claim 1. FIGS. 2A–2C provide concrete visual support for the hierarchical division steps of Claims 2, 12, and 13. FIG. 3's pseudocode supports the recursive implementation described in [0054]. FIG. 4's step-by-step flowchart maps to every operational limitation in Claim 13. The one gap is that no figure illustrates the CDF graph or the deviation measurement process recited in Claims 5, 10, and 16, leaving those limitations without direct visual support.
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Scorecard
Strategic Intent Scorecard
Multi-dimensional assessment of this application's patent strategy quality, based on claim structure, specification depth, and prosecution positioning.
Claim Breadth
3.5
Prosecution Defensibility
2.8
Spec–Claim Consistency
4
Dependent Claim Coverage
2.5
Claim Type Diversity
2.5
Figure Support Quality
3.5
Key observation: Spec–Claim Consistency is the highest-scoring dimension (4.0/5.0) because FIG. 4's detailed flowchart and FIG. 3's pseudocode provide direct, step-by-step support for every operational limitation in Claims 7 and 13, with paragraphs [0046]–[0051] explicitly mapping to the CDF-based determination limitations. The lowest score is Dependent Claim Coverage (2.5/5.0), because 9 of the 14 dependent claims simply repeat the same three determination criteria (CDF linearity, CDF deviation, mean/standard deviation) across three parallel chains without adding technically distinct fallback positions. Practitioners drafting continuations should file claims covering specific equalization method types (AHE, BBHE, DHE, as disclosed in [0053]) and binary vs. quadratic division distinctions (disclosed in [0028]) that the current dependent claims fail to capture.
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Critical Gaps
3 Critical Gaps in This Claim Set
A senior-attorney lens on the three highest-priority structural weaknesses — what each exposes in prosecution and litigation, and what a stronger filing would have done differently.
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3 Critical Gaps in This Claim Set
See the full attorney-level analysis of what this application leaves unprotected — and how to draft it more defensively for your own filings.
No CRM claim on recursive algorithm Dependent claims duplicate determination criteria Reference image size threshold left unprotected
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Disclaimer: This analysis is generated by PatSnap Eureka AI based on publicly available patent data from the USPTO. It does not constitute legal advice and should not be relied upon as such. Patent data may be subject to change as prosecution progresses. Scores and assessments reflect automated analysis and may not capture all relevant legal or technical nuances. Always consult a qualified patent attorney for formal legal opinions on patentability, freedom to operate, or infringement.
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